Will 2015 be the year that your enterprise be able to finally harness all of that customer data that they have compiled over the years? Will there be ways to organize and use this information to impact the bottom line? Indeed, this data has become a form of capital for enterprises. So what will change in 2015?
Big Data Brands to Watch
Here are the areas to watch: secure storage and backup with encryption, reliable data management and data visualization (DV) are key ingredients as far as next generation big data software is concerned.
As far as vendors are concerned, there are several players in the space including Twitter-owned Lucky Sort, Tableau, Advanced Visual Systems, JasperSoft, Pentaho, Infogram Tibco, 1010 Data, Salesforce, IBM, SAP, Hewlett-Packard, SAS, Oracle, Dell and Cisco Systems. These are a mix of independent and majors, but all have solid reputations in the industry. Choosing which one depends on numerous factors like budget, IT systems already in place, preference, reaquirements, etc.
The Coming Influx of Big Data
Big data must be useful and many professionals within all sorts of organizations are actively seeking out ways to use the data they have collected, rather than just consuming it.
Is your organization prepared for the influx of new users and devices that will flood the Internet and electronic communications, encapsulating customer interactions more than ever before? Many enterprises could be unprepared for the massive wave of data coming as billions of devices join the Internet. More devices, not just smartphones and computers, will be connected, bringing more data into organizations' servers.
Gartner reportedly estimated the Internet of Things, or IoT, market at 26 billion devices by 2020 and Cisco thinks it will add $14 trillion in economic value by 2020. These devices include everything from household and office electronics and appliances to industrial manufacturing equipment. IoT will increase big data exponentially. It will hit pretty much every industry in a big way, but planning and preparing for the road ahead can ensure at least some adaptability for 2015 and beyond.
How to Deal With Data
Assess your organization's needs thoroughly including a checklist of IT systems in place and what needs or opportunities exist there. IT management will likely find a multitude of ways to incorporate new systems or upgrades through the right software options. Try to find robust, dynamic systems that are tailored to the way information is used or may be used within and outside the organization. Also, explore ways to improve customer relationships through the targeting and taxonomy of their data. Big data will be a more useful asset in 2015.
After you have taken the time to make an assessment of need and checklist for problem areas, you have to implement changes so that you can make the most of your information. You want to absolutely make sure that the data that you have collected from customers, suppliers, personnel and others is accessible, useful and organized.
For example, a good search software that can access thousands of records and display results based on varying factors is a great way to handle the problem of search. Great search software is sometimes already a part of your organization’s CMS or other software for handling data and is just may not be fully utilized to make search more useful or easier.
Using Enterprise Search
Enterprise search applications vary by brand, but you may recognize a few of the names immediately from the larger tech firms such as IBM, HP and Microsoft. There are also open source options. Other vendors include Oracle, LucidWorks, Lexmark Perceptive Software, Sinequa and others. Sharepoint is probably one of the most popular options, which is also a tool for collaboration available from Microsoft. Google and IBM are also top companies in search technology. Many systems support multiple languages too.
HP is a great example of useful search for enterprise. Their flagship system is appropriately named Autonomy. Autonomy can index, or “crawl” (a search software term) millions of records including various types of content like documents, audio, video and social media. Employees and customers have come to expect a great system of search within their companies as expectations for technology have continued to climb higher due to a surge in search application use (such as Google searches on the web).
There are some important facets to search applications that should be noted. The HP Autonomy system, for instance, is capable of searching based on concept and context. This is becoming much more important in the era of big data. Searching through such large volumes of data requires some scrutiny to access the right information assets. Enterprise search applications can help with this obstacle.
Start with Little Data
It has been suggested that to deal with big data, you must first deal with little data. We are talking about metadata of course. Metadata are bits of information that can offer insight to content, helping to optimize search. Essentially it is information about information. Metadata can provide that context and concept information we referenced earlier in search applications.
Working with metadata can help with the overall process of keeping data organized and easy to access. The smaller pieces of information come together to become big information sets. Your team must start there to adequately solve this information overload problem.
Start by analyzing the exact needs or perceived functionality of the information. Taxonomy and terminology can be critical. Defining terms and putting them into contextual and conceptual order will help to provide a road map to access and utilize all of your team’s critical business data. This way, your data will actually become more valuable, too. Your information assets need to be managed in order to fully take advantage of them.
Some Big Data Tips
Here are some general tips to help with organizing and using your data assets:
- Perform usability testing of your organization’s tools for data management.
- Develop compliance and governance model for handling information.
- Develop master data management (MDM) plan to reinforce and promote compliance.
- Assess taxonomy and develop a controlled vocabulary to keep data structured.
- Compress files (such as PDF documents) when necessary to save on storage cost.
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