Business Intelligence/Big Data in 2013 and Beyond

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By Serhiy Haziyev, Director of Software Architecture at SoftServe, Inc. \\ December 2012

Business Intelligence & Big Data is a current hot trend among multiple technology enabled enterprises and ISVs. In this article we will briefly walk through the top three Business Intelligence trends and solutions that will undoubtedly be still important in 2013.

Over the past two years we have witnessed a rapid emergence of Business Intelligence, despite the fact that the term was coined as far back as 54 years ago by Hans Peter Luhn, a computer scientist at IBM.

In 2010-2011, Analytics and Business Intelligence held the 5th position in a Gartner rank of technologies that CIOs selected as organization priorities, right after Cloud Computing, Virtualization, Mobility and Social Media. Surprising as it may seem, for 2012 Business Intelligence was featured by Garner as number one priority for CIOs.

Figure 1 Gartner CIO survey for the past five years. Image credit: Courtesy of Gartner, Inc.

Apparently, the synergy of the Cloud Computing, Mobility and Social Media wave played a significant role in establishing BI as a current hot trend among multiple technology enabled enterprises and ISVs. Almost every software system produces data (which is usually stored), but this is especially true for Cloud and Social applications.

If data was equated to temperature in physical analogy, according to the second law of thermodynamics its accumulation would lead to the heat death of the universe. Fortunately, BI technologies are evolving at a rapid pace to keep up with the exponential raise of data and project complexity.

In this article we will briefly walk through the top three BI trends and solutions that will undoubtedly be still important in 2013.

Self-Service Business Intelligence

The reason why Self-Service BI is so attractive is that it allows end-users to build reports or dashboards without requesting IT to do so, thus making the process much faster, and the results – much more precise. At the early stages there were significant usability and performance challenges that slowed down the adoption of Self-Service solutions, but the introduction of In-Memory Analytics offered encouraging simplicity and power.

When the RAM memory became cheaper, innovative companies like QlikTech and Tableau received an incredible advantage at the Self-Service BI market. Nowadays almost all industry leaders include In-Memory analytics into their products in order to make them more competitive in the market – Microsoft (Power Pivot), SAP (Hana), IBM (Cognos) are just a few of them.

Cloud Business Intelligence

The recent Software-as-a-Service (SaaS) boom has created thousands of Cloud-based applications. Elimination of up-front costs as a result of a monthly or an annual subscription model lured business users in, and their data started flooding Cloud storages instead of being scattered somewhere on the customers’ premises.

Consequently, the further growth of user base and data accumulation generated a number of technical challenges for data storage & analysis as well as brand new business opportunities.

The topmost challenge is multi-tenancy, or ability to isolate and process the data of multiple customers in the same application. The essential challenge, of course, is delivering interactive reports and dashboards in a browser mode as the Cloud era demands.

A number of proprietary BI solution vendors (MicroStrategy, SAP BusinessObjects) as well as open-source vendors (JasperSoft, BIRT) have already created such a solution, and apparently in the near future we are going to see more BI vendors and their products supporting a Cloud model.

Big Data

Before we start discussing the current state of Big Data and making any predictions, it is worth mentioning that Big Data does not always mean analytics and BI. In general, most definitions agree that Big Data is data sets which are difficult to capture, store, search, share, analyze and visualize. While some of the mentioned activities do have a direct relation to Business Intelligence, the other ones such as capturing and storage may not require explicit analysis. For example, in the so called Next Generation Sequencing, a single person’s DNA file can take several terabytes, which makes the file management extremely difficult.

Another misconception is that the popular Hadoop software framework is a silver bullet for the Big Data challenge, even though Apache foundation community (the one incubating Hadoop) did a great job describing what Hadoop is Not. For the already mentioned example challenge of storing large DNA files, Network Attached Storage (NAS) is an absolutely adequate solution, while Hadoop would struggle with the task because of its low capturing performance and triple data replication redundancy.

The modern market offers multiple solutions for handling large data sets, including Hadoop as a backend and reporting tools built on top of it such as Jasper or Tableau; NoSQL databases such as Mongo DB or Cassandra; column-oriented storages such as HP Vertica or Teradata; and finally – Cloud solutions such as Google BigQuery. The fact is that every Big Data need requires thorough analysis and designing a solution that is sometimes based on a mix of different vendor products. Next year will most probably not change this status quo.

Conclusion

In this article we`ve discussed only three BI trends, but there are a few other trends worth mentioning in Predictive, Mobile, Operational and Sentimental Analytics fields. In general, according to the Gartner Magic Quadrant for BI, the market will continue to grow at a compound rate of 8.1% annually until 2015.

Among multiple industries that utilize BI, we are likely to see a boost in Healthcare, especially so in programs related to Meaningful Use, Pay-for-performance (P4P) and ACO (Accountable care organizations).

And finally, we will most probably witness a rise of the Agile Business Intelligence trend that leverages Self-Service BI, Cloud BI and data discovery dashboards to accelerate the time it takes to deliver value with BI projects.

References:

1. Worldwide BI, Analytics and Performance Management Revenue Estimates for 2011 by Gartner
2. Why QlikView In-Memory wins over OLAP Technology
3. SoftServe Realizes Advanced Big Data Reporting by Embedding Jaspersoft
4. Gartner Taps Predictive Analytics as Next Big Business Intelligence Trend
5. SoftServe Lowers Big Data Development Costs by 25 Percent with Jaspersoft

About the Author

Serhiy Haziyev is a Director of Software Architecture at SoftServe, Inc., a leading global provider of software development, testing and consulting services. Serhiy has more than 15 years of experience in enterprise-level solutions including SaaS/Clouds, Big Data, SOA and Carrier-grade telecommunication services. He specializes in software architecture methodologies, architectural patterns and software development practices for large and complex projects in healthcare and other industry verticals. Serhiy holds various qualifications including IBM Certified SOA Solution Designer and Microsoft Certified Professional. He is a frequent speaker at external and corporate conferences, where he conducts educational workshops sharing concepts and providing practical input to emerging technologies. Currently Serhiy leads, mentors and motivates the SoftServe Architecture Team consisting of more than 20 seasoned professionals.