The Power of Knowledge

Your contact center agents must be available and equipped with the knowledge they need to handle customer issues quickly and efficiently.

However, with the explosion of new channels such as Internet, social media, and mobile computing, many companies lack the tools and processes required to empower their employees to deliver great customer experience.

Organizations struggle with static, siloed knowledge systems that not only provide redundant, often inaccurate information, but are costly to maintain.

Companies that have invested in creating a Powerful State of Knowledge are delivering great customer experiences, which translate into sustainable growth and profitability.

To achieve powerful state of knowledge, companies must be able to:

1. Establish a single knowledge base. Consolidate your knowledge into one single source of truth and make it available to agents and customers across your web site, mobile, and social channels. Tie knowledge to analytics and key performance indicators (KPIs) to present valuable content and address information gaps. This new level of visibility makes it easy for agents to:

• Update knowledge
• Identify potential customer issues
• Provide fast, accurate resolution

If you become driven by market demand for enhanced self-help services and internal demand for efficient productivity improvements, you can transform your customer and employee support systems, taking your existing separate knowledge repositories and establishing one central cross-channel knowledge base. This solution will help to raise efficiency and reduce the cost-per-call of your agents, and it will also improve the quality of the customer support you provide to your customers.

2. Social media has evolved knowledge management from static data residing in a structured database to dynamic, unstructured data created in every social interaction. As a result, you must monitor customers’ social conversations on Facebook, Twitter, and other sites to analyze sentiment and prioritize and respond to service issues.

3. Not many organizations are using traditional knowledge base technology. Instead, many are attempting to embrace the chaos that Big Data, social media, and the move to the cloud create, yet they still face challenges bringing it all together to make the most out of the information.

Unified indexing and insight technology enables just that - tapping into full knowledge ecosystems and providing support agents, employees and customers with contextually relevant information. This unprecedented access to actionable insight has helped companies achieve dramatic results, such as a 30%+ reduction in case resolution time, 10%+ increase in customer self-service satisfaction and more.

The need to make the most of organizational knowledge, to get as much value from it as possible is greater now than ever before. Organizations of all sizes are finding themselves with overwhelming amounts of information, often locked away in silos--different systems, different departments, different geographies and different data types, making it impossible to connect the dots and make sense of critical business information.

Traditional KM initiatives have considered knowledge a transferable commodity that can be stored in a system of record and used mechanically. Yet, in reality, knowledge goes beyond data and information, and is personal and contextual.

Data is factual information measurements, statistics, or facts. In and of itself, data provides limited value. It must be organized into information before it can be interpreted. Information is data in context organized, categorized or condensed. Knowledge is a human capability to process information to make decisions and take action.

The building blocks of knowledge are everywhere, fragmented, complex, unstructured, and often outside the systems of record (in the cloud, in social media, etc.). The key is to bring it all together, and presenting it in context to users.

Unified indexing and insight technology is the way that forward thinking companies access knowledge and experts. The technology brings content into context--assembling fragments of structured and unstructured information on demand and presenting it, in context, to users.

Designed for the enterprise, unified indexing and insight technology is built to bring together data from heterogeneous systems (e.g. email, databases, CRM, ERP, social media, etc.), locations (cloud and on-premise), and varied data formats of business today, It securely crawls those sources, unifies the information in a central index, normalizes information and performs mash-ups on demand.

The technology can be context-aware, relying on the situation of the user to anticipate and proactively offer enriched, usable content directly related to the situation at hand such as solutions, articles, experts, etc. from across the vast and growing ecosystem.

Best Practices for a Higher Return on Knowledge

Bringing relevant content to your agents and customers will increase productivity, create happier employees and drive higher customer satisfaction. Follow these best practices to achieve a higher return on knowledge:

1. Consolidate the knowledge ecosystem. Bring together information from enterprise systems, data sources, employee and customer social networks, social media, etc. Connect overwhelming amount of enterprise and social information.

2. Connect people to knowledge in context. Connect users to the information they need, no matter where it resides, within their context and in real-time.

3. Connect people to experts in context. Connect the people associated with the contextually relevant content to assist in solving a case, answer a key challenge or provide additional insight to a particular situation.

4. Personalize information access. Present employees and customers with information and people connections that are relevant, no matter where they are, and no matter what they are working on.

Investing in the creation of a powerful state of knowledge builds a defensible advantage in delivering great customer experiences. Those experiences lead to sustainable growth and profitability by driving customer acquisition, customer retention, and operational efficiency.

Service and support agents can solve cases faster. No longer do agents need to search across multiple systems or waste time trying to find the right answer or someone who knows the answer. They will have relevant information about the customer or case at hand right at their fingertips: suggested solutions, recommended knowledge base articles, similar cases, experts who can help, virtual communication timelines, etc.

Customers can solve complex challenges on their own. Logging in to customer self-service, customers will see a personalized and relevant view of information form the entire knowledge ecosystem (from inside or outside your company) intuitively presented so that they can solve their own challenges.

Employees can stop reinventing the wheel. When every employee can access relevant information, locate experts across the enterprise, and know what does and does not exist, they can finally stop reinventing the wheel.

Galaxy Consulting has 16 years experience in this area. We have done this for few companies and we can do the same for you.

Personalization in Content Management

Content personalization in content management makes your users' experience more rewarding. Content personalization targets specific content to specific people. One simple example is showing code samples to developers and whitepapers to business users.

Segment Your Users

The first step to delivering a personalized customer experience is to segment your visitors so you can present them with what’s most relevant to them.

Any good personalization strategy starts with a fundamental understanding of your customer’s behavior, needs and goals. Upfront research goes a long way to building out the personas and having the insight from which to develop an approach to personalization. This may already be gathered through ongoing customer insight or voice of the customer programs, or be more ad hoc and project based. Regardless of the approach, be sure that any approach to personalization is grounded in a solid understanding of your users.

The next step in the process is to define the audience goals and objectives so you can know if the personalization efforts are successful. These may include top-line key performance indicators such as conversion rate or online sales, or be more specific to the personalization scenarios (i.e. landing page bounce rate). Try to be specific as possible and ensure that your measures of success directly relate to the areas of focus for your personalization efforts impact.

Personalize Your Content

In order to provide personalized content, it is necessary to determine which content is most effective for each audience segment. This content mapping process can be done alongside the audience segmentation model to ensure you have the right content for the right user at the right stage. If we use the business users and developers example from above, we can personalize the home page for the developers segment to talk about things related to the technology and how it can be extended while we serve business users with information related to how they can achieve their goals using this solution.

The biggest mistake organizations make with personalization is thinking too big and getting overwhelmed before they even start. It is exhausting to even start thinking about how to deliver the right message to the right person at every single interaction. Starting with a few specific personalization scenarios can help you more rapidly adopt the processes and technology and see what works on a small scale before expanding.

Here are a few example rules-based scenarios for an insurance company:

• If a user in a specific region of the United States visits the site, show them regionally specific rates and agent information.
• If a user has shown a specific interest in a vehicle, show images and offers that include that vehicle.
• If a user is an existing customer (as identified through specific site actions or e-mail campaigns) feature tools and content that help them maintain their relationship with you.
• If a user has already subscribed to the newsletter, replace the subscribe to newsletter call-out with a different offer or high value piece of content.

As you begin to think about the overall customer journey and digital experience, this list of scenarios is going to be far more detailed. However, it should not be more complicated than is necessary to accomplish the organizational goal of making it easier for audience segments to achieve their objectives while having the best possible user experience.

The process of content mapping and scenario planning will inevitably surface holes in the inventory of your existing content. Obviously, they will need to be filled. This will require some combination of recreating existing content for different audiences in addition to generating some which is completely new. Not to mention the ongoing process of updating and managing these content variations based on what’s working and what’s not.

Personalization in CMS

It would help to develop a content model and taxonomy for your CMS that is aligned to your audience segmentation approach. By tagging content appropriately you can often automate many areas of personalization. For example, display all white papers from a specific vertical industry.

Regardless of what tool is used to manage all of this complexity, it will require custom configuration. Some systems are naturally more user friendly than others but none of them come out of the box knowing your audience segments, content mapping, and scenarios. All of this information, once determined and defined, will need to be entered to the system.

Rules-based configuration is the most common type of work you’ll do with a CMS which is literally going through a series of "If, Then" statements to tell the CMS what content to show to what users. It’s important to have someone inside your organization or agency partner that owns the product strategy for personalization and can ensure it is consistently applied and within the best practices for that specific platform.

Sitefinity content management system has a simple interface for defining segments through various criteria such as where the visitor came from, what they searched for, their location, duration of their visit, etc. You can define custom criteria and have any combination of AND/OR criteria to define your segments.

Testing Your Personalization

Once your audience and content plans are sorted out and the technology is configured, it is time to test the experience from the perspective of each segment and scenarios within segments. You should test each variation on multiple browsers and mobile devices.

Some CMS allow to impersonate to test your results. For example, Sitefinity allows you to impersonate any segment and preview the customer experience on any device with the help of the mobile device emulators. This way you can be sure how your website looks like for every audience on any device.

Measure the Results

After you’ve segmented your audiences, personalized their experience and checked how your website/portal/CMS is presented for different audiences on different devices you should see the results of your work. They can be measured by the conversions and other website KPIs for the different segments compared to the default presentation for non-segmented visitors or to the KPIs prior to the personalization. Measuring will help you iterate and improve the results further.

Going forward it will be possible to revise previous assumptions with new information which is substantially more valid. Using the built-in analytics within your CMS or third party analytics, you’ll be able to watch how each segment interacts with the personalized content and if it was effective.

Galaxy Consulting successfully implemented content personalization for few clients. We can do the same for you. Contact us today for a free consultation.

Is Your Web Site Optimized for Mobile Devices?

Many people are highly dependent of their mobile devices for every day interactions, including mobile commerce. Our society is becoming highly mobile and connected. In the latest Shop.org and Forrester Research Mobile Commerce Survey, it's estimated that U.S. smartphone commerce will grow to $31 billion by 2016.

Those organizations that can best serve mobile customers will have an advantage in the competition. With a surge in mobile traffic comes the added potential to connect with and sell to customers through mobile commerce. Having a concrete mobile infrastructure plan and strategy is no longer an option, as it had been in recent years, but rather a must to compete in any customer-facing situation.

But despite this upward trajectory, retailers and other consumer-oriented companies still express some hesitancy about investing in multi-device environments. There is still some apprehension by companies, when it comes to moving forward with mobile planning. Companies still struggle to maintain uniformity across multiple device experiences when there are various screen sizes, operating systems, hardware specifications, and loading speeds to consider. One fear is that of the unknown, but security, data management, and simply proving a use case and subsequent return on investment are concerns as well.

The key issue in smartphone shopping continues to be the form factor, which can make navigation more difficult for customers. In addition to slower page load times on smartphones, some customers are concerned about the security of the transaction or simply complain that the experience just is not the same.

A successful mobile experience, like many other customer experiences, is about fulfilling customers' needs. First-time users of a mobile site or app tend to be less satisfied with their mobile experiences than frequent users because of their lack of familiarity with layouts, navigation, and functionality according to the survey of the mobile users. Knowing the different kinds of mobile devices customers use is critical. It is pertinent to develop a strategy that encompasses all types of customer scenarios.

Before embarking on any one mobile strategy, it is important to learn how your company's customers most likely would use their mobile devices. In addition to enabling customers to interact how they wish, any company looking to optimize its mobile presence must naturally consider the effects on the business as well, and how mobile usage will impact other lines of business and cross-channel marketing efforts.

In addition to justifying a use case and ROI for mobile, companies that wish to get into the mobile side of business must be aware of its limitations. Under ideal circumstances, companies want to engage with their customers and cultivate a one-to-one relationship while taking into consideration CANSPAM and privacy regulations. It is very important to adjust taxonomy and information architecture for the mobile experience. A lot of searches are made using mobile devices, so search also has to be optimized.

Optimizing your mobile site or developing a native application is no simple task. There are security considerations, as well as device-specific functions, to consider. Don't take a cookie-cutter approach. Some companies make the mistake of simply cloning online information without considering that consumer behavior on the mobile phone is dramatically different. Justify mobile ROI with consumer insight.

Consider security. Create a military-grade security infrastructure, while maintaining user-friendly design. Hire the best user interaction designer to design the security setup interaction.

Utilize mobile wisely. Once someone has discovered your brand through search, referral, or a marketing message, and they download the app, this may indicate a loyal customer. The app can be a great way to maximize and monetize that loyal relationship because it's in a controlled environment.

Galaxy Consulting has experience optimizing information architecture and search for mobile devices. Contact us today for a free consultation.

Data Lake

A data lake is a large storage repository and processing engine. Data lakes focus on storing disparate data and ignore how or why data is used, governed, defined and secured.

Benefits

The data lake concept hopes to solve information silos. Rather than having dozens of independently managed collections of data, you can combine these sources in the unmanaged data lake. The consolidation theoretically results in increased information use and sharing, while cutting costs through server and license reduction.

Data lakes can help resolve the nagging problem of accessibility and data integration. Using big data infrastructures, enterprises are starting to pull together increasing data volumes for analytics or simply to store for undetermined future use. Enterprises that must use enormous volumes and myriad varieties of data to respond to regulatory and competitive pressures are adopting data lakes. Data lakes are an emerging and powerful approach to the challenges of data integration as enterprises increase their exposure to mobile and cloud-based applications, the sensor-driven Internet of Things, and other aspects.

Currently the only viable example of a data lake is Apache Hadoop. Many companies also use cloud storage services such as Amazon S3 along with other open source tools such as Docker as a data lake. There is a gradual academic interest in the concept of data lakes.

Previous approaches to broad-based data integration have forced all users into a common predetermined schema, or data model. Unlike this monolithic view of a single enterprise-wide data model, the data lake relaxes standardization and defers modeling, resulting in a nearly unlimited potential for operational insight and data discovery. As data volumes, data variety, and metadata richness grow, so does the benefit.

Data lake is helping companies to collaboratively create models or views of the data and then manage incremental improvements to the metadata. Data scientists and business analysts using the newest lineage tracking tools such as Revelytix Loom or Apache Falcon to follow each other’s purpose-built data schemas. The lineage tracking metadata also is placed in the Hadoop Distributed File System (HDFS) which stores pieces of files across a distributed cluster of servers in the cloud where the metadata is accessible and can be collaboratively refined. Analytics drawn from the data lake become increasingly valuable as the metadata describing different views of the data accumulates.

Every industry has a potential data lake use case. A data lake can be a way to gain more visibility or to put an end to data silos. Many companies see data lakes as an opportunity to capture a 360-degree view of their customers or to analyze social media trends.

Some companies have built big data sandboxes for analysis by data scientists. Such sandboxes are somewhat similar to data lakes, albeit narrower in scope and purpose.

Relational data warehouses and their big price tags have long dominated complex analytics, reporting, and operations. However, their slow-changing data models and rigid field-to-field integration mappings are too brittle to support big data volume and variety. The vast majority of these systems also leave business users dependent on IT for even the smallest enhancements, due mostly to inelastic design, unmanageable system complexity, and low system tolerance for human error. The data lake approach helps to solve these problems.

Approach

Step number one in a data lake project is to pull all data together into one repository while giving minimal attention to creating schemas that define integration points between disparate data sets. This approach facilitates access, but the work required to turn that data into actionable insights is a substantial challenge. While integrating the data takes place at the Hadoop layer, contextualizing the metadata takes place at schema creation time.

Integrating data involves fewer steps because data lakes don’t enforce a rigid metadata schema as do relational data warehouses. Instead, data lakes support a concept known as late binding, or schema on read, in which users build custom schema into their queries. Data is bound to a dynamic schema created upon query execution. The late-binding principle shifts the data modeling from centralized data warehousing teams and database administrators, who are often remote from data sources, to localized teams of business analysts and data scientists, who can help create flexible, domain-specific context. For those accustomed to SQL, this shift opens a whole new world.

In this approach, the more is known about the metadata, the easier it is to query. Pre-tagged data, such as Extensible Markup Language (XML), JavaScript Object Notation (JSON), or Resource Description Framework (RDF), offers a starting point and is highly useful in implementations with limited data variety. In most cases, however, pre-tagged data is a small portion of incoming data formats.

Lessons Learned

Some data lake initiatives have not succeeded, producing instead more silos or empty sandboxes. Given the risk, everyone is proceeding cautiously. There are companies who create big data graveyards, dumping everything into them and hoping to do something with it down the road.

Companies would avoid creating big data graveyards by developing and executing a solid strategic plan that applies the right technology and methods to the problem. Hadoop and the NoSQL (Not only SQL) category of databases have potential, especially when they can enable a single enterprise-wide repository and provide access to data previously trapped in silos. The main challenge is not creating a data lake, but taking advantage of the opportunities it presents. A means of creating, enriching, and managing semantic metadata incrementally is essential.

Data Flow in the Data Lake

The data lake loads extracts, irrespective of its format, into a big data store. Metadata is decoupled from its underlying data and stored independently. This enables flexibility for multiple end-user perspectives and maturing semantics.

How a Data Lake Matures

Sourcing new data into the lake can occur gradually and will not impact existing models. The lake starts with raw data, and it matures as more data flows in, as users and machines build up metadata, and as user adoption broadens. Ambiguous and competing terms eventually converge into a shared understanding (that is, semantics) within and across business domains. Data maturity results as a natural outgrowth of the ongoing user interaction and feedback at the metadata management layer, interaction that continually refines the lake and enhances discovery.

With the data lake, users can take what is relevant and leave the rest. Individual business domains can mature independently and gradually. Perfect data classification is not required. Users throughout the enterprise can see across all disciplines, not limited by organizational silos or rigid schema.

Data Lake Maturity

The data lake foundation includes a big data repository, metadata management, and an application framework to capture and contextualize end-user feedback. The increasing value of analytics is then directly correlated in increase in user adoption across the enterprise.

Risks

Data lakes therefore carry risks. The most important is the inability to determine data quality or the lineage of findings by other analysts or users that have found value, previously, in using the same data in the lake. By its definition, a data lake accepts any data, without oversight or governance. Without descriptive metadata and a mechanism to maintain it, the data lake risks turning into a data swamp. And without metadata, every subsequent use of data means analysts start from scratch.

Another risk is security and access control. Data can be placed into the data lake with no oversight of the contents. Many data lakes are being used for data whose privacy and regulatory requirements are likely to represent risk exposure. The security capabilities of central data lake technologies are still in the beginning stage.

Finally, performance aspects should not be overlooked. Tools and data interfaces simply cannot perform at the same level against a general-purpose store as they can against optimized and purpose-built infrastructure.

Careful planning and organization of data lake strategy is required to make this project a success.

What is New in SharePoint 2016?

Microsoft releases a new version of SharePoint every three years. SharePoint 2016 public Beta version is available. The full version is expected in Spring 2016. Here is what is new in SharePoint 2016 version.

SharePoint 2016’s main goal is to bring the best of Office 365 Cloud technology to on-premises solutions. In this truly effective Hybrid model, organizations will be able to have the best of the Cloud, whilst keeping all their important information and data stored on-premises.

SharePoint Server 2016 has been designed to reduce the emphasis on IT and streamline administrative tasks, so that IT professionals can concentrate on core competencies and mitigate costs. Tasks that may have taken hours to complete in the past have become simple and efficient processes that allow IT to focus less on day-to-day management and more on innovation.

Main Focus

User Experiences

• Mobile experiences
• Personalized insights
• People-centric file storage and collaboration

Infrastructure

• Improved performance and reliability
• Hybrid cloud with global reach
• Support and monitoring tools

Compliance

• New data protection and monitoring tools
• Improved reporting and analytics
• Trusted platform

MinRoles

You can now install just the role that you want on particular SharePoint 2016 servers. This will only install what’s required there, and it will make sure that all servers that belong to each role are compliant. You will also be able to convert servers to run new roles if needed. You can look at the services running on the SharePoint 2016 server and see if they are compliant.

Downtime for Updates

Downtime previously required to update SharePoint servers has been removed.

Mobile and touch

Making decisions faster and keeping in contact are critical capabilities for increasing effectiveness in any organization. The ability for end users to access information while on the go is now a workplace necessity. In addition to a consistent cross-screen experience, SharePoint Server 2016 provides the latest technologies and standards for mobile push and information synchronization. With deep investment in HTML5, SharePoint 2016 provides capabilities that enable device-specific targeting of content. This helps to ensure that users have access to the information they need, regardless of the screen they choose to access it on.

SharePoint 2016 further empowers users by delivering a consistent experience across screens, whether using a browser on the desktop or a mobile device. Through this rich experience, users can easily transition from one client to another without having to sacrifice features.

App Launcher

The App Launcher provides a new navigation experience where all your apps are easily available from the top navigation bar. You can quickly launch your application, browse sites and access your personal files.

Improved Controls

Based on SharePoint Online and OneDrive for Business, SharePoint 2016 document libraries inherit the improved control surface for working with content, simplifying the user experience for content creation, sharing and management.

Content Sharing

SharePoint 2016 improves the sharing experience by making it more natural for users to share sites and files. You can just click the "Share" button at the top right corner of every page, enter the names of people you want to share with, and press Enter. The people you just shared with will get an email invitation with a link to the site.

SharePoint still uses powerful concepts like permission levels, groups and inheritance to provide this experience. Part of sharing is also understanding who can see something. If you want to find out who already has access to a particular site, you can go to the "Settings" menu in top right corner, click "Shared with", and you will see the names and pictures of people who have access to the site.

Large File Support

SharePoint 2016 provides support for uploading files up to 10GB.

Compliance Tools

Preventing data loss is non-negotiable, and over-exposure to information can have legal and compliance implications. SharePoint 2016 provides a broad array of features and capabilities designed to make certain that sensitive information remains that way, and to ensure that the right people have access to the right information at the right time.

New In-Place Hold Policy and Document Deletion Centers will allow you to manage time-based, organization-wide in-place hold policies to preserve items in SharePoint and OneDrive for Business for a fixed period of time, in addition to managing policies that can delete documents after a specified period of time.

Cloud Hybrid Search

Cloud hybrid search offers users the ability to seamlessly discover relevant information across on-premises and Office 365 content. With the cloud hybrid search solution, you index all your crawled content, including on-premises content, in your search index in Office 365. When users query your search index in Office 365, they get unified search results from both on-premises and Office 365 cloud services with combined search relevancy ranking.

Cloud hybrid search provides some key benefits to customers of both SharePoint 2013 and early adopters of SharePoint 2016 IT preview, such as:

• the ability to reduce your on-premises search footprint;
• the option to crawl in-market and legacy versions of SharePoint, such as 2007, 2010 and 2013, without requiring upgrade of those versions;
• avoiding the cost of sustaining large indexes, as it is hosted in Office 365.

With this new hybrid configuration, this same experience will also allow users to leverage the power of Office Graph to discover relevant information in Delve, regardless of where information is stored. You will not only be able to get back to all the content you need via Delve, but also discover new information in the new Delve profile experiences and even have the ability to organize content in Boards for easy sharing and access.

You will have to use the Office 365 Search for this to work. If SharePoint 2016 On-Premises users query against their On-Premises Search service, it will continue to give them local results only.

However, once available, this will allow users to fully embrace experiences like Delve in Office 365 and more to come in the future.

OneDrive Redirection

With SharePoint 2016, you can redirect your My Sites to your Office 365 subscription’s OneDrive for Business host. In other words, if a user clicks on OneDrive, he will be redirected to his Office 365 My Site and no longer to his On-Premises. Although you can use document libraries in on-premises SharePoint, Microsoft's larger strategy pushes users to use OneDrive to manage files across all devices. This creates the ability to integrate that OneDrive cloud storage into your on-premises SharePoint.

Follow Sites

Now users can click on “Follow” both On-Premises and on their Office 365 and see them all in one place under the “Sites” app in the App Launcher.

Site Folders

The OneDrive for Business area aims to bring users to one place to help them work with their files regardless of where they are. You will also be able to navigate your Sites and their libraries from there.

Content Management Systems Review - Vasont

Vasont is a component content management system. It has powerful capabilities to store, update, search, and retrieve content. It offers version control, integrated workflows, project management, collaborative review, translation management, and reporting to manage content and business processes.

Vasont provides opportunities for multi-channel publishing and editing in your favorite applications. In addition, it provides an advanced editorial environment built to maximize, manage, and measure content reuse. Unicode support enables multi-language implementations. It also integrates the ability to process content with reusable, event driven business logic as an integral part of the system.

Content is stored in an underlying Oracle database and can be imported, exported, and stored in a variety of formats, including XML, SGML, HTML, as well as other formats that are required as input documents or deliverable formats. This is possible because Vasont can store content separately from any specific tagging structure.

Vasont can be used to store and manage embedded multimedia in structured content. It can also be used to provide a consistent organization and hierarchy to unstructured business documents and other digital assets to provide an overall document management solution. Vasont stores both component-level graphics and unstructured business documents as multimedia components.

Content can be stored at a document or sub-document level and with any content assets such as graphics and references. Vasont has great power at the component level with content organized using XML as input and output. Content can be manipulated and reused at any level of granularity. It is easy to add metadata to existing content and take advantage of the richness that metadata can provide.

Vasont also excels at integrating XML and non-XML traditional document content to provide powerful content applications that can cross departmental or functional boundaries. It is effective in a variety of content scenarios or in combined scenarios, including:

• highly structured XML or SGML content;
• structuring unstructured information assets such as in regulatory environments;
• documents, especially linked to workflow and business logic;
• digital assets such as graphics.

Vasont allows the building of content within and among these content relationships and content scenarios. It provides the power to model information in an organization and share it across different divisions. It stores all types of content in one repository. For example, structured content (i.e. XML, HTML, SGML, text and pointers), multimedia files, unstructured documents (i.e., Word, Excel, PDF files, graphics).

In Vasont Administrator, an administrator can set up the rules of structure and apply any processing options needed to transform, validate, or redirect data. The administrator can store settings for loading, extracting, editing and viewing data; user permissions; and workflow. Administrative responsibility can be assigned to specific Associate Administrators so that multiple groups or departments can share the system and yet control their own setups.

The system includes Vasont Universal Integrator (VUI) for Arbortext Editor, Adobe FrameMaker, JustSystems XMetaL, Quark XML Author, or Microsoft Word. The VUI allows authors to work in a familiar environment and provides a frequently used subset of functionality available in Vasont to simplify the editing process.

Vasont High-Level Application Architecture

Main parts are User Navigator and Content Navigator. Users, their roles and permissions are set up using User Navigator. Content Navigator includes content definitions, content instances, workflow definitions, load and extract views, and business logic which is processing options.

There is Vasont Application Programming Interface (API) for advanced customization and integration. The Vasont API allows for development of:

• custom user interfaces;
• web access to Vasont;
• processing options;
• Daemons.

Vasont Daemon Programs provides background processing routines that automate repetitive tasks such as extracting and loading content. Some customization is required to implement it.

Content Model

The content model and the corresponding rules of structure are defined by the administrator in the Vasont Administrator. These rules usually correspond closely to the structure rules defined in a Document Type Definition (DTD) or schema, but they may differ somewhat or may support multiple DTDs for different outputs. Structures may also be defined in Vasont, independent of a DTD, which is useful when storing documents and other digital assets that may need to be organized in a specific way but are not structured XML or SGML content. The rules of structure help guide you through the editing process by allowing you to place components in only the appropriate locations in a collection.

The Vasont Administrator is also used to define the big picture of how collections will be organized in Vasont, through the creation of content types and collection groups. These categories are represented in a tree or list view in Vasont and have symbols that represent them. This screen of a tree view shows the sequencing and grouping of collections.

The detailed items in a collection are called components. The top component in each tree view is called the primary. Normally a collection will contain many primaries.

Vasont has several classes of components and components can be broken down into smaller chunks, depending on the needs of the organization. The level of chunking is called granularity. It is essential to understand how your Vasont system has been configured so that you can find and edit the relevant material and maximize reuse. Granularity describes the smallest chunk of content stored in Vasont. A high level of granularity means that content is stored in large chunks. For example, you may have Book, Chapter, and Section components with no components defined at a level lower than Section. On the other hand, a very granular setup stores content in very small chunks, typically broken down into paragraph-level components or the equivalent.

Content types are the highest level of organization in Vasont and often serve as major divisions in content. Typically, different content types store content with very different content models, such as content used in different divisions or groups within a corporation. Content types are set up in the Vasont Administrator.

Content in each content type is organized into collections and optional collections groups. Inside of a content type called Publication, a collection such as Manuals is a grouping of similar content that follows the same structure. Depending on how similar the content model is, collections and collection groups within a single content type may share content. Collections in the same content type have similar content models so that content can be reused, moved, and referenced. Content in collections from different content types may be reused if the content types share similar raw components. Pointers are allowed from components in one collection to components in another collection and the collections can be in different content types.

Components are reusable chunks of content defined in the rules of structure for each collection. Although not required to, components usually correspond to elements in a document type definition (DTD). The three types of components are: text, multimedia, and pointer.

Metadata, or information about your content, helps you automate business logic and categorize, locate, filter, and extract content. Traditional types of metadata for topics include index entries that describe content or identifiers that can be used for cross-referencing or mapping context-sensitive help in software applications. Other examples of metadata include labeling content that applies to a particular customer or vendor, whether content should be published to an online help system or a printed manual, or other types of classifications. Metadata can be information that helps perform automated business logic through the use of Vasont Processing Options.

The Vasont Navigator provides an intuitive way to view, edit, reuse, and search content within a collection. Its hierarchical structure represents the organization of content in the system and icons indicate the state of items, including whether they have been included in a log. Components may be opened and closed individually or in groups. Open multiple Navigator windows to drag and drop content easily from one location to another, either within or across collections, rather than scrolling up and down the tree view.

Vasont provides powerful search capabilities to find and reuse content across the entire organization. The search function allows to search for content across collection boundaries. When performing a cross-collection search, you are prompted to select the collections to search and then specify query criteria for the content desired.

The Vasont Content Ownership feature gives a designated user the right to assign ownership to an individual user, or a group of users which provides the exclusive right to alter specified content. The designated user will have the right to assign ownership to a Primary component. Once ownership is assigned, the Vasont CMS then recognizes users who have permission to perform add/delete/change actions to the content, and prevents those who do not have ownership permissions from making changes to the content.

Each and every piece of unique content is stored in the raw material only once. Vasont compares content in the same raw component or in aliased raw components to determine if the content has been used in more than one instance. If the text of the components is the same, it is stored in the raw material as a single component. Vasont's ability to automatically reuse content where it can, without any specific setup, is called implicit reuse.

Depending on your setup, you may explicitly reuse content by referencing or “pointing to” relevant content from different contexts. For example, you may have a collection of shared procedure components that you can point to rather than storing the entire procedure in multiple locations.

Vasont can be used to store and manage embedded multimedia in structured content. It can also be used to provide a consistent organization and hierarchy to unstructured documents and other digital assets to provide an overall document management solution. Vasont stores both component-level graphics and unstructured documents as multimedia components.

Vasont offers a Translation Package that enables users to lower their overall translation costs by minimizing the amount of content that needs to be translated. This is possible because it keeps track of content that has already been translated and insures it is not re-translated. It also measures the amount of savings for each translation project by identifying the percentage of words that have already been translated.

It offers Translation Management that helps users manage projects and sub-projects by tracking dates, vendors, languages and status information. A translation project is a module of content that is being translated into multiple languages (i.e., a topic that is being translated into French, German, and Chinese). The sub-projects are each individual language to which the module is being translated (i.e., the specific French translation is a sub-project of the topic translation project).You can submit your projects for quote or send them for translation directly from Vasont's translation window. This window also provides word counts for each translation project.

Integration with translation vendors can be used with this package for an automated content delivery back and forth from Vasont. The translation package is used to consolidate the status information for all your translation projects in one place so you can keep your projects on schedule and lower your costs.

Humanizing Big Data with Alteryx

In my last post, I described Teradata Unified Data Architecture™ product for big data. In today's post, I will describe Teradata partner Alteryx which provides innovative technology that can help you to get the maximum business value from your analytics using the Teradata Unified Data Architecture.™

Companies can extract the highest value from big data by combining all relevant data sources in their analysis. Alteryx makes it easy to create workflows that combine and blend data from relevant sources, bringing new and ad hoc sources of data into the Teradata Unified Data Architecture™ for rapid analysis. Analysts can collect data within this environment using connectors and SQL-H interfaces for optimal processing.

Create Business Analytics in an Easy-to-Use Workflow Environment

Using the design canvas and step-by-step, workflow-based environment of Alteryx, you can create analytics and analytic applications. With a single click, you can put those applications and answers to critical business questions in the hands of those who need them most. And when business conditions and underlying data change, Alteryx helps you iterate your analytic applications quickly and easily, without waiting for an IT organization or expensive statistical specialists.

Base Your Decisions on the Foresight of Accessible Predictive Analytics

Alteryx helps you make critical business decisions based on forward-looking, predictive analytics rather than past performance or simple guesswork. By embedding predictive analytics tools based on the R open source statistical language or any of the in-database analytic capabilities, Alteryx makes powerful statistical techniques accessible to everyone in your organization through a simple drag-and-drop interface.

Understand Where and Why Things Happen: Location Matters

Whether you are building a hyper-local marketing and merchandizing strategy or trying to understand the value of social media investments, location matters. Traditionally, this type of insight has been in the hands of a few geo specialists focused on mapping and trade areas. With Alteryx, you can put location specific intelligence in the hands of every decision maker.

With the rise of location-enabled devices such as smart phones and tablets, consumer and business interactions increasingly include a location data-point. This makes spatial analysis more critical than ever before. Alteryx provides powerful geospatial and location intelligence tools as part of any analytic workflow. You can visualize where events are taking place and make location-specific decisions.

Alteryx can push custom spatial queries into the Teradata Database to leverage its processing power and eliminate data movement. You can enrich your spatial data within the Teradata system using any or all of these functions provided by Alteryx:

• geocoding of data;
• drive-time analytics;
• trade area creation;
• spatial and demographic analysis;
• spatial and predictive analysis;
• mapping.

Alteryx simplifies the previously complex tasks of predictive and spatial analytics, so every employee in your organization can make critical business decisions based on real, verifiable facts.

Deliver the Right Data for the Right Question To The Right Person

To answer today’s complex business questions, you need to access your sources of insight in a single environment.That is why Alteryx allows you to bring together data from virtually any data source, whether structured, unstructured or cloud data, into an analytic application. Using Alteryx, you can extend the reach of business insight by publishing applications that let your business users run in-database analytics and get fast answers to their pressing business questions.

Teradata and Alteryx: Powerful Insights for Business Users

To exploit the opportunities of all their data, organizations need flexible data architectures as well as sophisticated analytic tools. Analysts need to rapidly gather, make sense of and derive insights from all the relevant data to make faster, more accurate strategic decisions. But given the variety of potential data sources, it is difficult for any single tool to be most effective at capturing, storing and exploring data. Using the Teradata Unified Data Architecture™ with Alteryx enables you to explore data from multiple sources, as well as the ability to deploy the insights derived from the data.

You can create sophisticated analytics, taking advantage of new, multi-structured data sources to deliver the most ROI. The combined solution:

• integrates and addresses both structured and emerging multi-structured data Leverages the Teradata Integrated Data Warehouse, Teradata Aster Discovery platform and Hadoop to optimal advantage;
• creates both in-database and cross-platform analytics quickly without requiring specialized SQL, MapReduce or R programming skills;
• lets you combine the capabilities of the Alteryx environment with routines developed in other analytical tools within a single analytical workflow;
• easily deploys analytics to the appropriate users beyond the analyst community.

The combined solution of Alteryx and the Teradata Unified Data Architecture™ provides an IT-friendly environment that supports the need to analyze data found inside and outside the data warehouse. Analysts and business users can leverage powerful engines to create and execute integrated applications. This kind of analysis is only possible with an environment that can bring together routines created by separate tools and running on different platforms.

Enhancing the Teradata Unified Data Architecture™ with the speed and agility of Alteryx creates a powerful environment for traditional and self-service analytics using integrated data and massively parallel processing platforms. It delivers:

• a complete solution for the full life-cycle of strategic and big data analytics, from transforming, enriching and loading data to designing analytic workflows and putting easy-to-use analytic applications in the hands of business users;
• improved ability to manage and extract value from structured and multi-structured data;
• ability for business analysts to create data labs and perform predictive and spatial analytics on the Teradata data warehouse and Teradata Aster discovery platforms;
• faster analytical processing within applications using in-database analytics in Teradata and SQL MapReduce functions in Teradata Aster.

The Alteryx solution helps customers with the Teradata Unified Data Architecture™ achieve these benefits by providing the following:

• robust set of analytical functions;
• access to a rich catalog of horizontal and industry-specific analytic applications in the
• Alteryx Analytics Gallery;
• syndicated household, demographic, firmographic, map and Census data to enrich existing sources;
• native data integration and in-database analytical support for Teradata data warehouse and Teradata Aster capabilities;
• ability to leverage Teradata SQL-H™ for accessing Hadoop data from Aster or Teradata Database platforms.

Use Case: Predicting and Preventing Customer Leave

Problem

A global communication service provider is interested in preventing customers leaving by identifying at-risk customers and providing special offers that reduce the likelihood of leaving in a profitable way. To do this, they need predictive analytics.

Solution

Teradata and Alteryx deliver an end-to-end analytic workflow process from data consumption and analysis to application deployment. Alteryx integrates and loads call detail records from diverse sources along with customer data from the Teradata warehouse into the Aster database to create a complete, rich data set for iterative analysis. You can run iterative discovery analysis to determine the key indicators behind customer leaving and loyalty. These key indicators are captured as repeatable applications to enrich the data warehouse with leaving and loyalty scores. In addition, the discovery analysis is captured and deployed to the business users as a parameterized application for further iterative analysis.

Key Solution Components

• Aster Discovery platform for deep analytics and segmentation;
• Teradata data warehouse to operate and deploy insights and enriched data across the enterprise;
• Alteryx for the user workflow engine to orchestrate data blending and analytics.

Benefits

• Ability to identify key customers that are likely move candidates;
• determine problem spots on the network (cell sites, network elements) that are driving move;
• discover other key reasons for move (performance, competitive offers);
• discover which offers have prevented churn for similar customers in the past;
• identify which offers will work and evaluate a least-cost offer to prevent move;
• ability to make offers to keep customers from leaving;
• deeper understanding of customer behavior.

Teradata - Analytics for Big Data

Successful companies know that analytics is the key to winning customer loyalty, optimizing business processes and beating their competitors. 

By integrating data from multiple parts of the organization to enable cross-functional analysis and a 360-degree view of the customer, businesses can make the best possible decisions. With more data and more sophisticated analytics, you can realize even greater business value.

Today businesses can tap new sources of data for business analytics, including web, social, audio/video, text, sensor data and machine-generated data. But with these new opportunities come new challenges.

For example, structured data (from databases) fits easily into a relational database model with SQL-based analytics. Other semi-structured or unstructured data may require non-SQL analytics, which are difficult for business users and analysts who require SQL access and

iterative analytics.

Another challenge is identifying the nuggets of valuable data from among and between multiple data sources. Analysts need to run iterations of analysis quickly against differing data sets, using familiar tools and languages. Data discovery can be especially challenging if data is stored on multiple systems employing different technologies.

Finally, there is the challenge of simply handling all the data. New data sources often generate data at extremely high frequencies and volumes. Organizations need to capture, refine and store the data long enough to determine which data to keep, all at an affordable price.

To exploit the competitive opportunities buried in data from diverse sources, you need a strong analytic foundation capable of handling large volumes of data efficiently. Specifically, you need to address the following three capabilities:

Data Warehousing - integrated and shared data environments for managing the business and delivering strategic and operational analytics to the extended organization.

Data Discovery - discovery analytics to rapidly explore and unlock insights from big data using a variety of analytic techniques accessible to mainstream business analysts.

Data Staging - a platform for loading, storing and refining data in preparation for analytics.

Teradata Unified Data Architecture™ product includes a Teradata data warehouse platform and the Teradata Aster discovery platform for analytics, as well as open-source Apache Hadoop for data management and storage as needed.

Data Warehousing

The Teradata Active Enterprise Data Warehouse is the foundation of the integrated data warehouse solution. This appliance works well for smaller data warehouses or application-specific data marts.

Data Discovery

For data discovery, the Teradata platform uses patented SQL-MapReduce® on the Aster Big Analytics Appliance, providing pre-packaged analytics and applications for data-driven discovery. Mainstream business users can easily access this insight using familiar SQL-based interfaces and leading business intelligence (BI) tools. If you are performing discovery on structured data, a partitioned data lab in the data warehouse is the recommended solution.

Data Staging

Hadoop is an effective, low-cost technology for loading, storing and refining data within the unified architecture. However, Hadoop is not designed as an analytic platform.

The Teradata Data Warehouse Appliance and the Teradata Extreme Data Appliance offer cost-effective storage and analytics for structured data. The Teradata Unified Data Architecture™ integrates these components into a cohesive, integrated data platform that delivers the following capabilities:

• unified management of both structured and unstructured data at optimal cost;
• powerful analytics spanning SQL and MapReduce analytics;
• seamless integration with the existing data warehouse environment and user skillset.

The Teradata Unified Data Architecture™ handles all types of data and diverse analytics for both business and technical users while providing an engineered, integrated and fully supported solution.

conceptClassifier for SharePoint

conceptClassifier for SharePoint is the enterprise automatic semantic metadata generation and taxonomy management solution. It is based on an open architecture with all APIs based on XML and Web Services. conceptClassifier for SharePoint supports all versions of SharePoint, SharePoint Online, Office 365, and OneDrive for Business.

Incorporating industry recognized Smart Content Framework™ and intelligent metadata enabled solutions, conceptClassifier for SharePoint provides a complete solution to manage unstructured and semi-structured data regardless of where it resides.

Utilizing unique compound term processing technology, conceptClassifier for SharePoint natively integrates with SharePoint and solves a variety of business challenges through concept identification capabilities.

Key Features

• Tag content across the enterprise with conceptual metadata leveraging valuable legacy data.
• Classify consistent meaningful conceptual metadata to enterprise content, preventing incorrect meta tagging.
• Migrate tagged and classified content intelligently to locations both within and outside of SharePoint.
• Retrieve precise information from across the enterprise when and how it is needed.
• Protect sensitive information from exposure with intelligent tagging.
• Preserve information in accordance with records guidelines by identifying documents of record and eliminating inconsistent end user tagging.

Components

conceptClassifier

Both automated and manual classification is supported to one or more term sets within the Term Store and across content hubs.

conceptTaxonomyManager

This is an advanced enterprise class, easy-to-use taxonomy and term set development and management tool. It integrates natively with the SharePoint Term Store reading and writing in real-time ensuring that the taxonomy/term set definition is maintained in only one place, the SharePoint Term Store. Designed for use by Subject Matter Experts, the Term Store and/or taxonomy is easily developed, tested, and refined.

Term Set Migration tools are also a component of conceptTaxonomyManager that enable term sets to be developed on one server (e.g. on-premise server) and then migrated to another server (e.g. Office 365 server) in an incremental fashion and preserving all GUIDs. This is a key requirement in migration.

conceptSearch Compound Term Processing Engine

Licensed for the sole use of building and refining the taxonomy/term set, the engine provides automatic semantic metadata generation that extracts multi-word terms or concepts along with keywords and acronyms. conceptSearch is an enterprise search engine and is sold as a separate product.

SharePoint Feature Set

Provides SharePoint integration and an additional multi-value pick-list browse taxonomy control enabling users to combine free text and taxonomy browse searching.

Products

These are base platform and optional products that are needed to solve your particular business process challenge and leverage your SharePoint investment.

Search Engine Integration

This functionality is provided via conceptClassifier for SharePoint to integrate with any Microsoft search engine being used within SharePoint. conceptClassifier for SharePoint also supports integration with most non-SharePoint search engines and can perform on the fly classification with search engines calling the classify API.

Search engine support includes SharePoint, the former FAST products, Solr, Google Search Appliance, Autonomy, and IBM Vivisimo. If the FAST Pipeline Stage is required, this is sold as a separate product.

Intelligent Document Classification

This functionality is provided via conceptClassifier for SharePoint, to classify documents based upon concepts and multi-word terms that form a concept. Automatic and/or manual classification is included.

Content managers with the appropriate security can also classify content in real time. Content can be classified not only from within SharePoint but also from diverse repositories including File Shares, Exchange Public Folders, and websites. All content can be classified on the fly and classified to one or more taxonomies.

Taxonomy Management and Term Store Integration

With the Term Store functionality in SharePoint, organizations can develop a metadata model using out-of-the-box SharePoint capabilities. conceptClassifier for SharePoint provides native integration with the term store and the Managed Metadata Service application, where changes in the term store will be automatically available in the taxonomy component, and any changes in the taxonomy component will be immediately available in the term store.

A compelling advantage is the ability to consistently apply semantic metadata to content and auto-classify it to the Term Store metadata model. This solves the challenges of applying the metadata to a large number of documents and eliminates the need for end users to correctly tag content. Utilizing the taxonomy component, the taxonomies can be tested, validated, and managed, which is not a function provided by SharePoint.

Intelligent Migration

Using conceptClassifier for SharePoint, an intelligent approach to migration can be achieved. As content is migrated, it is analyzed for organizationally defined descriptors and vocabularies, which will automatically classify the content to taxonomies, or optionally the SharePoint Term Store, and automatically apply organizationally defined workflows to process the content to the appropriate repository for review and disposition.

Intelligent Records Management

The ability to intelligently identify, tag, and route documents of record to either a staging library and/or a records management solution is a key component to driving and managing an effective information governance strategy. Taxonomy management, automatic declaration of documents of record, auto-classification, and semantic metadata generation are provided via conceptClassifier for SharePoint and conceptTaxonomyWorkflow.

Data Privacy

Fully customizable to identify unique or industry standard descriptors, content is automatically meta-tagged and classified to the appropriate node(s) in the taxonomy based upon the presence of the descriptors, phrases, or keywords from within the content.

Once tagged and classified the content can be managed in accordance with regulatory or government guidelines. The identification of potential information security exposures includes the proactive identification and protection of unknown privacy exposures before they occur, as well as monitoring in real time organizationally defined vocabulary and descriptors in content as it is created or ingested. Taxonomy, classification, and metadata generation are provided via conceptClassifier for SharePoint.

eDiscovery, Litigation Support, and FOIA Requests

Taxonomy, classification, and metadata generation are provided via conceptClassifier for SharePoint. This is highly useful when relevance, identification of related concepts, vocabulary normalization are required to reduce time and improve quality of search results.

Text Analytics

Taxonomy, classification, and metadata generation are provided via the conceptClassifier for SharePoint. A third party business intelligence or reporting tool is required to view the data in the desired format. This is useful to cleanse the data sources before using text analytics to remove content noise, irrelevant content, and identify any unknown privacy exposures or records that were never processed.

Social Networking

Taxonomy, classification, and metadata generation are provided via conceptClassifier for SharePoint. Integration with social networking tools can be accomplished if the tools are available in .NET or via SharePoint functionality. This is useful to provide structure to social networking applications and provide significantly more granularity in relevant information being retrieved.

Business Process Workflow

conceptTaxonomyWorkflow serves as a strategic tool managing migration activities and content type application across multiple SharePoint and non-SharePoint farms and is platform agnostic. This add-on component delivers value specifically in migration, data privacy, and records management, or in any application or business process that requires workflow capabilities.

conceptTaxonomyWorkflow is required to apply action on a document, optionally automatically apply a content type and route to the appropriate repository for disposition.

An additional add-on product, conceptContentTypeUpdater is deployed at the site collection level, can be used by site administrators, and will change the SharePoint content type based on results from pre-defined workflows and is used only in the SharePoint environment.

Where does conceptClassifier for SharePoint fill the gaps?

• SharePoint has no ability to automatically create and store classification metadata.
• SharePoint has no taxonomy management tools to manage, test, and validate taxonomies based on the Term Store.
• SharePoint has no auto-classification capabilities.
• SharePoint has no ability to generate semantic metadata and surface it to search engines to improve search results.
• SharePoint has no ability to automatically tag content with vocabulary or retention codes for records management.
• SharePoint has no ability to automatically update the content type for records management or privacy protection and route to the appropriate repository.
• SharePoint has no ability to provide intelligent migration capabilities based on the semantic metadata within content, identify previously undeclared documents of record, unidentified privacy exposures, or information that should be archived or deleted.
• SharePoint has no ability to provide granular and structured identification of people, content recommendations, and organizational knowledge assets.

Leveraging Your SharePoint Investment

When evaluating a technology purchase and the on-going investment required to deploy, customize, and maintain, the costs can scale quickly. Because conceptClassifier for SharePoint is an enterprise infrastructure component, you can leverage your investment through:

• Native real-time read/write with the term store.
• Ability to implement workflow and automatic content type updating.
• Reduce IT Staff requirements to support diverse applications.
• Reduce costs associated with the purchase of multiple, stand-alone applications
• Deploy once, utilize multiple times.
• Rapidly integrated with any SharePoint or any .Net application.
• Used by Subject Matter Experts, not IT staff, does not require outside resources to manage and maintain.
• Eliminate unproductive and manual end user tagging and the support required by business units and IT.
• Reduce hardware expansion costs due to scalability and performance features.
• Deployable as an on-premise, cloud, or hybrid solution.

Leveraging Your Business Investment

The real value of your investment includes both technology and the demonstrable ROI that can be generated from improving business processes. conceptClassifier for SharePoint has been deployed to solve individual or multiple challenges including:

• Enables concept based searching regardless of search engine.
• Reduces organizational costs associated with data exposures, remediation, litigation, fines and sanctions.
• Eliminates manual metadata tagging and human inconsistencies that prohibit accurate metadata generation.
• Prevents the portability and electronic transmission of secured assets.
• Assists in the migration of content by identifying records as well as content that should have been archived, contains sensitive information, or should be deleted.
• Protects record integrity throughout the individual document lifecycle.
• Creates virtual centralization through the ability to link disparate on-premise and off-premise content repositories.
• Ensures compliance with industry and government mandates enabling rapid implementation to address regulatory changes.

Benefits

The combination of the Smart Content Framework™, conceptClassifier for SharePoint, and the deployment of intelligent metadata enabled solutions result in a comprehensive and complete approach to SharePoint enterprise metadata management. Specific benefits are:

• Eliminate manual tagging.
• Improve enterprise search.
• Facilitate records management.
• Detect and automatically secure unknown privacy exposures.
• Intelligently migrate content.
• Enhance eDiscovery, litigation support, and FOIA requests.
• Enable text analytics.
• Provide structure to Enterprise 2.0.