Mid-market businesses bet big on big data technology
Mid-market enterprises are swiftly warming up to Big Data technology. A recent study shows that as much as 43 percent of the global mid-market businesses are either investing in Big Data technology or looking into it.
The study conducted by Techaisle ‘Big Data Adoption & Trends’ study, which is a survey of 3,360 mid-market businesses across different geographies, shows that the promise of superior data-driven decision making is motivating almost half of the global mid-market businesses. Out of these, 18 percent are actively investing in Big Data-related projects. The possibilities of analysing a variety of data sources and producing action-driven business insights are too big to ignore for mid-market businesses.
North America is largest market
The current and planned investment represents a sizable opportunity considering that the segment is relatively new and requires a certain level of IT sophistication and a history in linear investment in Information Technology enablers to be successful. North America has both the largest market and the highest level of investment in Big Data overall in SMB and mid-market segments. Mid-Market attitude towards Big Data transitions from “Over-Hype” to “Must-Have” technology with the increase in employee size. However, nearly one-fourth of lower mid-market businesses consider Big Data to be over-hyped and yet 29 percent think that it will be an important part of their business decision-making process in the future.
Business intelligence by itself has provided enough business insights, however, mid-market businesses are now looking for extracting business perspectives to drive superior decisions and ultimately achieve superior results. Extracting business perspectives has become important as they rethink their marketing strategies because mobility, social media, and other transactional services have increased the number avenues for connections with their customers and partners.
In addition to understanding customers, mid-market businesses are also considering big data analytics as an important initiative to help them improve operational efficiencies.
Big expectations from big data analytics
The study shows that there are many different tactical objectives for deploying big data projects but the top among them are sentiment monitoring, generating new revenue streams and improving predictive analytics. It must also be said that businesses have figured out that there is a lot of publicly available data, which could also be analysed to their advantage.
The mid-market businesses actively investing in big data technologies are expecting some clear cut benefits from big data analytics such as increased sales, more efficient operations and improved customer service. These objectives differ slightly by different geographic regions. As the growth rates continue to lag in mature economies, the pressure to increase revenue grows resulting in developing robust analysis and extracting insights from all sales and customer data including transactions.
When specifically asked about preferred deployment choice in terms of on-premise vs. cloud, mid-market businesses are unsure as they are still navigating through their technology options. However, Hadoop dominates as the preferred platform but confusion exists.
In terms of analytics skill-set and long-term vision, the potential of linking structured and unstructured data sources to create new business insights is being considered very useful but at the same time mid-market businesses are not really prepared for it. In fact one-third of mid-market businesses agree that linking structured and unstructured data would be very useful for big data analytics but over 70 percent mention that they have either none or very limited capabilities of analyzing unstructured data. This is where they are turning to external help for guidance.
Challenges of big data technology deployment
Needless to say, survey reveals that big data deployment is posing tremendous challenges. Technology confusion, lack of skilled resources and potential unclean data are being considered as the biggest roadblocks for big data project implementations. Big data technology and its far-reaching capabilities are being viewed by mid-market businesses as very complex resulting in very steep learning curves.
In spite of challenges, the study shows that there have been some successes when business units, IT and data analysts exhibit extraordinary alignment. Highest success rates for project implementation and generating new insights have been achieved when IT and data analysts work with external consultants from project inceptions.
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