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Trends in Data Warehousing and Business Intelligence

Originally published September 16, 2008

In today’s customer-centric market, enterprises are required to anticipate customer trends well in advance to measure up to the ever-increasing customer expectations. With the breadth and depth of choices constantly evolving, the influences that affect customers’ buying decisions are multidimensional in nature.

Thus, understanding of the customers (and their different segments) along with a clear understanding of one’s own organization’s drawbacks and strengths in meeting the customer demands has gained paramount significance in recent times. Business still needs to operate and continuously strive to increase profits, reduce cost, mitigate risk, adhere to legal and regulatory compliance, and constantly try to understand the changing customers’ needs and serve them efficiently.

It is against this backdrop that organizations are trying to collect as much data as possible about themselves, their business processes, their customers (buying patterns/behaviors) and their product and service offerings.

To understand the entire ecosystem surrounding the customer and to make timely decisions, organizations today are witnessing an exponential growth in data, as well as an upsurge in the rate at which data is being collected. Coupled with this, the myriad range of products and tools available to sustain a complete business intelligence (BI) life cycle, and the issues surrounding data quality and data integration have started cropping up at the enterprise-level.

In such an environment, I have tried to list some of the observed trends in the data warehousing (DW) and business intelligence industry that have either occurred in the not-so-distant past, or currently exist or will accelerate in the ensuing months. These trends (shown in Figure 1) are not mutually exclusive and are by no means exhaustive. I expect this list to evolve, grow, and constantly change to keep up with the developments in the industry.


Figure 1: Data Warehouse and Business Intelligence Trends

As shown in Figure 1, I have tried to classify these trends into five buckets, namely:

  • Hardware (includes virtualization, appliances, mobile devices for receiving and interacting with BI systems)

  • Software (DBMS advances, XML standards, visualization techniques)

  • Convergence (of various technologies, services and business models such as SaaS, increasing popularity of open source adoption, SOA)

  • Consolidation (consolidation of companies in the data warehousing and business intelligence industry into five or six dominant players, as well as consolidation of DW and BI tools and vendors within a company)

  • Other (increasing need for quality education in the DW and BI industry and stronger alignment of IT with business)

In the future, as you walk into my café (the Trends in Data Warehousing and Business Intelligence channel) to sip your favorite cup of tea or coffee or, perhaps, to enjoy a glass of malted beverage (DW and BI trends), you might hear discussions, views or debates around some of the topics listed in Figure 1. Whether it is to analyze the impact of enterprise data management (EDM) – which, in my view, encompasses data architecture and modeling, data security, data governance, master data management (MDM), metadata management and data quality in its core framework – on BI, or to taste some of the cool new advances in the field of DBMSs, my objective will always be to provide you with the freshest of blends of these trends, with the best customer experience.

And, I do encourage you to visit some of my neighboring cafés (other contributors/channels on BeyeNETWORK.com) to savor the spread provided there. I look forward to your company in enriching the café’s experience by providing your valuable comments and feedback.

Till then, so long, and as Bartles & Jaymes would say, “... and thank you for your support.” 

SOURCE: Trends in Data Warehousing and Business Intelligence

  • Ajay BhargavaAjay Bhargava
    Ajay has more than 20 years of industry, research, mentoring and teaching experience in areas relating to databases, data warehousing (DW), business intelligence (BI) and data mining. His career started with working on database product development with companies such as Novell, Pervasive Software and BMC Software. He has been Novell’s chief database architect to standards organizations such as SQL Access Group (SAG), ODBC and IDAPI, and has been doing strategy consulting and implementation in areas of BI and DW since 1998 to various customers in retail, banking and financial services, telecom and insurance. As adjunct faculty at the University of Texas (UT) in Austin, he has taught a database design course for 4 years. Ajay is currently heading Enterprise Data Management (EDM) Services at TCS and teaches an undergraduate database management systems (DBMS) course at the College of Engineering in Pune. He can be reached at ajaybhargava00@yahoo.com.

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Posted September 9, 2011 by Dhananjay Singh

Thanks a lot, excellent read and well summarized.

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