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Is Big Data A Big Deal? 3 Ways To Make Data & Analytics Work For Your Business

by Srikant Gokulnatha, Co-Founder & Chief Product Officer, Numerify September-2015

Founded in 2012, Numerify is a California headquartered provider of IT Business Analytics applications.

The allure of big data is undeniable. With the promise of accelerating innovation and bringing products to market more quickly, companies have sought ways to leverage big data to gain a competitive edge. However, businesses must also consider how big data fits in with their specific business model, if at all. While big data approaches are essential to highly-connected enterprises like Amazon that are constantly generating and driven by enormous amounts of information, that doesn't mean big data is appropriate for every organization.

Is Big Data For You?

You've got lots of data, and it's tempting to wonder what hidden answers will reveal themselves once the right systems are in place. But does it make sense to apply the same techniques that have worked for the biggest web-scale companies?

Let's first clarify what we mean by big data. While scale is key, it also entails the coupling of powerful databases with information storage technology and analytical tools. Moreover, it typically involves a high level of automation via algorithms to generate correlations and extract insights beyond human effort.

The problem for many organizations is there simply may not be enough data. What may initially seem like an enormous amount of data, in the larger context may prove insufficient raw material to generate enough meaningful insights to justify a slow and costly big data project.

In many cases, companies overlook the greater value in analyzing medium and small data sets, where most relevant data is already structured. This is especially true for businesses that do not resemble Fortune 500 companies with high data volumes, the budgets to dedicate to big data projects, or the wherewithal to experiment with myriad technologies still in flux (e.g. Spark vs. Hadoop).

Making Big Data Work For You

So if companies are not quite ready to jump on big data in the same way as large retailers, governmental agencies, manufacturers, or healthcare companies, then what should they do? Here are three strategies for ensuring your data works for you:

  1. Bigger Insights from Smaller Data:

    Organizations may find that they are not fully realizing the value in smaller, more structured data sets. According to Forrester Research, most companies are only analyzing 12 percent of their existing data, ignoring 88 percent of data. By narrowing their focus to more relevant areas, they can deliver greater immediate value.

    This doesn't mean that companies cannot benefit from technologies and strategies borne of big data. Regardless of scale, organizations can realize gains from highly-performant databases designed for larger data sets, such as RedShift.

    More importantly, big data has brought a greater focus on strategies that work across all data sets. The automation of analytic processes and offloading of mundane tasks associated with managing data, means that humans can focus on the why instead of the what. Other concepts central to big data, such as predictive analysis, data mining, and the correlation of disparate data have become equally useful in small data applications.

  2. Big Business Focus

    Many organizations unprepared to undertake an all-encompassing big data project find that they benefit from "going big" in a very targeted way. Rather than a data-agnostic approach, these organizations have made a conscious effort to narrow their focus on a single business unit or data set which they've determined will make the most impact. For instance, with IT spend growing to 5 percent of revenue, many companies have chosen to tackle this oft-overlooked department to make a big impact on the bottom line. Focusing on smaller targets allows smaller organizations to still make a big impact.

  3. Bigger Engagement

    Big data often relies on data scientists to generate algorithms and interpret data. But one lesson all businesses can learn from big data is greater accessibility and the democratization of data. Tools developed for big data have made it possible to turn unstructured and unrelated data into insights that could be leveraged in novel ways.

    Similarly, companies focused on smaller data sets can more fully realize the potential of their efforts by empowering all consumers of data. Pre-built, domain-specific analytic solutions like Numerify for IT or InsightSquared for Sales make it possible for non-technical business users to interpret the data themselves. In many cases, these solutions allow them to directly interact with the data, drill down, and generate their own correlations, insights, and predictions. By making data more accessible to the collective talent and intellectual curiosity of the larger organization, companies can achieve much bigger insights.

In the end, it's not about big data or small data. It's about choosing an analytic solution that makes the most sense for your business. Big data has made tremendous strides from which all analytics benefit. Fortunately, the increase in analytic capabilities has also resulted in greater choice. Big data technology is no longer only for Big Enterprises. Organizations of all sizes now have solutions available to them that incorporate the best of both worlds and the potential to rapidly change the direction of their business.