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The Convergence of Social Media, Business Intelligence and Big Data Industry Trends and How They Affect Midmarket Companies, Part 1

Originally published June 12, 2012

Throughout the year I attend many end user conferences and industry events. Because vendors can be forward looking and focus on achieving their roadmaps, there is always talk about the trends in the market. Whether on the information or business side, one thing that becomes obvious when speaking with customers, partners, and general business intelligence (BI) users is that in many cases, there is a general gap between what solutions offer and how organizations are applying business intelligence within their companies.

There are several reasons for this:

  1. To remain competitive, vendors need to stay ahead of the curve and consistently develop and enhance their solution offerings, which may be faster than the speed by which organizations will upgrade or expand their solutions.

  2. Mature BI users request updates to products and want to take advantage of newer technologies that may not yet be applied more widely in the market.

  3. Broader IT expansions enable BI vendors to create enhanced applications by taking advantage of cloud computing, better processing speeds, newer database technologies, etc.

  4. BI customers and potential customers may not be aware of what is available and how to get there.
And the list goes on...

The most effective way for organizations to take advantage of technology trends is to understand how these trends affect the market and how to leverage them to enhance performance. In addition, there are cases where trends might not apply to your business. Overall, understanding what exists in the market, why it’s important and how it may apply to your business can provide the most value within the organization. This article will be in three parts:  Part one explores the convergence of social media and business intelligence, as well as big data. Part two will look at cloud computing, mobility and the expansion of analytics. Part three will provide a broader look at the effects of these trends on the market by discussing the rising demands of organizations, how it affects broader software development, and the increasing difficulties of software selection.

The Complexities of Social Business Intelligence

The term ‘social business intelligence’ can cover many things. Within business intelligence specifically, there are three major applications of social-related information and interaction. Social business intelligence (also called collaborative business intelligence) encompasses the ability to interact with business intelligence in a way that mimics social networking. For instance, to communicate more broadly with colleagues, business users may want to be able to chat about performance issues in real-time or add notes that can be attached to peaks and values within various charts and graphs. Ideally, the concept is the broadening of BI adoption through ease of use and interactivity by developing solutions that have similar collaborative features found on online communities, etc.

Beyond this are the various types of analytics associated with social media, which represents the second type of social BI-related use. Social network analysis is becoming more widely used within organizations to identify how their social networks work and how to take advantage of key customers who are major influencers. For instance, the ability to identify communication patterns of smartphone users, how they communicate with one another and who is connected to whom provides a telecommunications company with a broader understanding of who uses what services when, and whether they are influencers of adoption for others. Based on this information, telcos (telephone companies) can provide incentives to these users or target marketing campaigns more successfully.

The final way organizations apply social business intelligence is by leveraging social network platforms such as Facebook and Twitter to identify sentiment analysis and market trends. This may involve looking at the number of likes, identifying hashtags or analyzing the sentiment of comments. People are generally vocal on these platforms in terms of what they like and don’t like, making it easy for businesses to identify issues proactively, deal with any customer complaints and identify their successes.

The implications of these options for organizations are two-fold. First, only certain applications will apply within any given organization. Yes, every business has customers, but social network analysis may not apply, and depending on who is using the BI tools internally, adding collaborative functionality may not be the best approach. For instance, much financial or fraud detection data is private and controls need to be placed on how that information is accessed and shared. Second, technology now exists that allows companies to use what is externally available to help drive better decision making. For example, the potential to identify customer sentiments through text analytics and social media access exists in a way that was never available before.

Big Data

Big data involves managing large amounts of machine-related data that are complex, diverse and potentially versatile (commonly referred to as volume, velocity, variety and variability). Hadoop and MapReduce are two of the common frameworks that help centralize distributed data sources. The BI market also has its plethora of database technologies that help store, process and analyze these big data sets. How data is stored, consolidated and accessed will differ for each solution. Consequently, aside from many organizations trying to figure out how to take advantage of big data, the other question really involves the number of companies that require big data applications at all.

As more and more dashboard and analytics vendors support big data, the identification of how or if it should be applied becomes even more important to ensure that solutions are properly addressing business needs. The ability to support multiple TBs of data has been in existence for several years. The added complexities that exist with real-time and diverse data sources are what make the concepts surrounding big data unique. Organizations evaluating solutions need to take into account what their data requirements are and whether solution providers can meet those needs. Not all businesses need to address big data because not all businesses experience big data challenges. However, all businesses face challenges that necessitate the need for business intelligence.


The business-related link between social business intelligence and big data is that many complexities exist to gain valuable insights from either of these initiatives. Over time these trends have become more broadly applied within organizations. On a superficial level, it seems like big data is further along in terms of beneficial use, but as more social applications become the norm within business applications, organizations will begin to adopt BI platforms that are conducive to broader collaboration as well as use analytics to access social content.

  • Lyndsay WiseLyndsay Wise

    Lyndsay is the President and Founder of WiseAnalytics, an independent analyst firm specializing in business intelligence, master data management and unstructured data. For more than seven years, she has assisted clients in business systems analysis, software selection and implementation of enterprise applications. Lyndsay conducts regular research studies, consults, writes articles and speaks about improving the value of business intelligence within organizations. She can be reached at lwise@wiseanalytics.com.

    Editor's Note: More articles and resources are available in Lyndsay's BeyeNETWORK Expert Channel. Be sure to visit today!

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