Huge volumes of data that are streaming in from numerous sources are making it possible for companies of all sizes to use data analysis and data discovery tools and techniques to gain deeper insights about market trends and customer behaviors.
Still, a common assumption is that the tools and expertise needed to take advantage of these opportunities are restricted to the largest enterprises with the resources and capital to do so, according to a recent Aberdeen Group report.
In fact, 51% of respondents from small companies (less than $50 million in revenue) cite the expense of software and services as the primary inhibitor preventing them from investing in and improving their data environments, according to the report.
However, additional research by Aberdeen Group finds that the same tools and techniques used by large enterprises to provide fast, scalable data analysis with big data are also being utilized by small companies.
The four technological areas that are critical to success with big data initiatives are data integration, in-memory computing, unstructured data management, and data visualization. Fortunately, there are affordable options for each of the four areas.
Data silos that arise between business lines and organizational functions continue to pose problems for decision makers who want to gain a 360-degree view of customers as well as views of the enterprise and the various business inputs that they can analyze to determine the health and condition of different areas of the company.
Still, there are ways to conduct data integration cost effectively.
As we’ve pointed out, part of the challenge that many companies face are issues associated with data latency to ensure that the most timely and relevant information is being blended together. There are inexpensive tools on the market that can be used to help with this, including those that can be used to create enterprise data mashups.
Meanwhile, reasonably-priced in-memory computing tools can be used to examine data sets that are stored entirely within a computer system’s memory, enabling business leaders to obtain much faster query response times against big data.
In addition, affordable data visualization tools make it possible for all types of end users – from senior executives to mid-level managers – to make sense of torrents of structured and unstructured data and to spot previously unknown market or customer trends.
As Deloitte consultants Eric Openshaw and JR Reagan point out in a guest column for Financial Times, more efficient processing and decreasing technology costs are making different types of visualization possible for all types of companies.
Large and small companies alike that have taken the big data plunge are seeing impressive returns on their investments.
Organizations of different sizes that have implemented big data initiatives report a 12% year-over-year improvement in operating profit and and they’ve increased their total customer bases by over 14% over the past fiscal year, according to Aberdeen Group. On average, these performance improvements are more than 26% better than for companies that haven’t embarked on big data efforts.
Bottom line: Making use of big data analytics doesn’t have to mean breaking the bank.
