Data for the King: the status, hotspots and trends of business intelligence

Business Intelligence (bi,business FDI) can be traced back to 1958, when IBM researcher Hans Peter Luhn first presented the concept of business intelligence in an IBM magazine article.

But until the 1980 's, the Decision Support System (DSS) began to become popular, the 1990 business intelligence theory began to prevail, the industry uses business intelligence to collectively refer to the following areas of software innovation: including performance management, planning, reporting, query, analysis, online analysis processing, operation system integration, predictive analysis.

The market scale of business intelligence

In recent years, in order to achieve new cost savings and growth plans, companies invest heavily in business intelligence programs, digging into spreadsheets and data from a variety of systems (legacy systems, internal islands, customer relationships, suppliers, partners, etc.) to get close to real-time operational analysis results (including historical analysis and future forecasts).

In general, the business intelligence market can be defined in five dimensions: capacity, speed, type, abstraction, complexity. On the market segmentation of Business Intelligence, TDWI gives a very simple model as follows:

Business Intelligence Model Diagram

Business Analytics, corporate performance management and the business intelligence software market grew by 13.4% in 2010 to $10.5 billion, according to a Gartner Business intelligence market Analysis. Businesses are investing in business intelligence software platforms to answer three key questions: How are we doing? Why? What are we going to do?

The 2012 business intelligence market is expected to grow strongly, with IBM's one CIO survey showing that business intelligence tops the list of corporate IT spending priorities. Other big data will also drive the growth of business intelligence-hardware and software such as Oracle's Eadata, IBM's Netezza, SAP's Hana, and EMC's greenplum are hot spots in the analysis market at this stage. Industry applications such as retail business (including E-commerce) customer analysis and forecasting analysis demand is strong.

Business intelligence Market Size data Source: Gartner

Revenue ranking of business intelligence companies (top five)

Gartner's report also shows that the software market for business intelligence has not changed much since 2009. SAP is leading 22.9% per cent of its market share (thanks to a 2007 acquisition of Business One), with Oracle taking 15.6% of the runner-up and SAS ranking third in 13.2%. It is noteworthy that IBM, while 11.6% of the market share in the fourth, but IBM has recently made data analysis as a strategic focus, the acquisition of a range of companies including Cognos, SPSS, ILog, CoreMetrics, Algorithmics, openpages , FCX Bae, Emptoris, DemandTec, etc.

With IBM's "crazy" takeover of the business intelligence market, its market share is expected to rise rapidly, and IBM also has strategic assets such as Watson and DB2. IBM is focusing on the value chain of business Intelligence: RAW data-> Data Integration-> Intelligence-> perspective-> decision-making, creating formidable competitiveness. IBM sees "managing data, understanding data, and data based decisions" as a 20 billion dollar business.

The current situation of business intelligence market

According to Gartner, the "Big Four" of business Intelligence: SAP, Oracle, IBM and Microsoft, will continue to dominate the market, totaling 59% of the market share. In the field of Business intelligence platform and Enterprise performance management (CPM), the "Big Four" occupies more than two-thirds of the market share. In the pure statistical and analytical application market, SAS still dominate.

Business intelligence tools for enterprise IT organizations are becoming integrated (visualization, ETL, reporting, data warehousing), but new data visualization tools and business analytics applications are emerging. Memory analytics and mobile Business Intelligence (BI) are two emerging and fast-growing branches. At the same time, the use of ipad-based analytics, known as "CxO Analytics", is also very robust for business users.

Enterprise users are not very concerned about the brand of business intelligence products, they value the ease of use of these products, functionality and the speed of the market. Enterprise users also reject products and programs that require longer implementation cycles. Frustrated by the performance, availability, and latency of conventional business intelligence applications, enterprise users are more likely to purchase specialized data-all-in-one machines, such as Oracle's Exadata.

Gartner analyst Dan Sommer believes business intelligence will be at the heart of corporate information initiatives as corporate governance moves toward "information driven". The business intelligence market is expected to accelerate growth in 2012 to 2013 years.

Business Intelligence Market Detailed data

Specific business intelligence market share data are as follows:

Business Intelligence market share data

Gartner calculates market share with software only and does not include system integration and professional services as well as specialized hardware and software (such as large data Hadoop,bi, SSD). However, it is not clear whether Gartner calculates social media analytics and online analytics services (Analytics as a Service,aaas).

Here is the four-quadrant business Intelligence Magic from Gartner: 2009,2010,2011

Four quadrants of business intelligence magic

Six driving forces in the growth of the business intelligence market

performance, availability, and latency issues. The three major issues of traditional business intelligence have stimulated the sales of data analysis machines, such as Oracle's Exadata, EMC's Greenplum and IBM's Netezza. The current mainstream performance enhancement is the allocation of I/O-intensive processing to dedicated all-in-one machines, which drastically reduce the latency of applications, such as SAP's bussinessobjects, through technology such as caching. Enterprise's demand for real-time data perspective. Real-time analysis of the desire to stimulate manufacturers to develop a memory analysis and other technologies and related products, but also stimulate the development of predictive analysis technology, in addition to mobile analysis, Cloud Analysis (AaaS) and large data are the future market hotspots. Upgrade cycle. According to IDC's analysis, the enterprise application market is entering a decade-by-generation cycle, and companies are faced with the choice of continuing to use stable but functional, original business intelligence applications, or embracing new technologies such as large data, cloud computing and memory analytics, but may have new applications for bugs. Continuous investment in basic data and information management. These are the underlying work of business intelligence, including data discovery, modeling, integration, cleanup, and database optimization, which are time-consuming exhausting dirty live dirty. Data integration and merger integration. Corporate mergers and acquisitions will spur sales of related business intelligence solutions. And as David Kreutter, vice president of Pfizer, says, analytics is becoming more of an operational business than it was in the past. Large data. According to Wikibon's report, the big data market will maintain a staggering 58% growth in the next five years. As a business intelligence platform and application related to large data will also benefit.

The future belongs to businesses that can control the entire data lifecycle-where does the data come from, how it is collected and used, and where?

We are entering the era of "data is king" from "content is king", but all these are inseparable from business intelligence. Business intelligence tools make data easier to manage, store, maintain, and categorize. Better access to data can help companies make informed decisions, and as data collection becomes easier, the size, speed, and type of data are growing at a high speed, and companies will begin to look at how to use these data rationally to establish new competitive advantages in an increasingly unpredictable economic environment.

(Responsible editor: Duqing first)