Today, large companies as well as small and medium-sized businesses (SMBs) use business intelligence (BI), a data analysis process aimed at boosting business performance by helping key decision makers collect, store, retrieve and analyze data to make better-informed decisions. A key component of BI analytics initiatives is the tools that are used to help a company assess its business processes, performance, market trends and other factors in order to improve corporate strategies and internal operations.
BI analytics tools can be roughly divided into three categories:
- Reporting tools generate report-type information in an electronic format that typically supports finance-associated organizational planning, budgeting and performance management processes. These tools range in sophistication from simple report generators such as SAP Crystal Reports to the reporting software built into elaborate enterprise resource planning (ERP) suites such as SAP R/3 and Oracle's E-Business Suite.
- Querying tools run frequently used queries to provide analysis of data down to a certain level, as in the case of IBM Cognos or SAP Business Objects.
- Sophisticated analytics tools do "deeper-dive" data analysis using such approaches as predictive analytics (e.g., SAS and IBM SPSS).
Surrounding and supporting these tools is a BI analytics infrastructure, which should be designed to ensure access to a broad range of data -- including on the Web and in public clouds. Vendors such as IBM and Microsoft provide support for querying public-cloud data stores and Hadoop big data systems, along with mobile-device support and software; they also offer ways to integrate these technologies with existing BI and analytics systems in-house. BI architectures typically also include rapid-query-generation development tools, rapid infrastructure build-out capabilities and integration tools to combine data from different data sources (e.g., Cisco Composite Server).
Many large enterprises have a data warehouse or equivalent networked data marts at the core, which provides greater data control. Cost is often a factor for SMBs, however, as they often don't have a data warehouse and must depend on outside vendors -- for example, value-added resellers or service providers offering multi-tenant applications on the cloud -- to provide an equivalent BI suite.
The BI analytics tools market
Today's BI analytics market is dominated by a few large vendors with a broad array of products and extensive infrastructure offerings. These include IBM, Oracle, SAP and Microsoft. Smaller vendors such as MicroStrategy (OLAP-based querying), Birst (public-cloud BI analytics) and SAS (reporting and statistical analysis) offer competitive tool sets with a narrower focus, while upstart companies such as QlikTech, Tableau Software and Tibco Software's Spotfire unit have made a splash with self-service BI and data discovery tools.
A new entrant to the market in late 2014 was Salesforce.com, with its Wave product. Salesforce Wave applies analytics to sales, marketing and customer service processes and aims to provide a ground-up redesign of querying tools to allow less sophisticated business users to carry out self-service BI using a mobile-like querying interface and a simplified, common representation of a wide variety of data sources.
How BI analytics software is sold
Buyers should anticipate that the line between BI analytics software suites and related markets such as enterprise content management will become increasingly blurry. There will be no simple one-size-fits-all product that supports BI and analytics applications.
Negotiating with the larger vendors will typically involve initial design and customization efforts on the part of both buyer and seller. Even in public-cloud cases, you typically can't build an adequate BI analytics system yourself, so you must deal with vendor offerings that include things beyond BI and analytics software. When the cloud isn't the only part of the sale, use of implementation services, as well as ongoing provisioning support, is likely to be on the table.
With those caveats, it's still true that the primary solution that BI analytics vendors are selling is a software product suite. Buying criteria (which will be discussed more fully in a separate article) should include such things as ease of implementation, security and privacy concerns, functionality, flexibility, and cost.
The benefits of BI analytics
BI and analytics processes form the core of most companies' efforts to leverage information to gain competitive advantages, reduce operational risks and costs, and identify and fine-tune business strategies. More specifically, well-designed BI analytics systems give C-suite executives a 360-degree view of the organization, often with near-real-time updates and alerts; that provides a strong platform for business process analysis and redesign, on-the-fly performance management and agile marketing. In addition, they can be used to incorporate feedback from internal end users and external customers into improving such areas as help desk operations and customer experience management.
The primary users of BI analytics tools are upper management -- such as CFOs and chief marketing officers -- as well as business analysts and other people on their staffs in the marketing and finance departments. For the CFO, reporting is now a keep-the-business-running tool, while analytics allows the CFO to give the CEO insights that show, for example, how business strategies are affecting the quarterly results (and why), and how the company compares to competitors. According to executive-suite surveys conducted by IBM and other companies, typical CMOs have seen a large upgrade in their importance to the CEO as a result of analytics insights; they can alert the CMO and hence the CEO to customer problems, and identify new markets and new sales and marketing tactics. For example, a McKinsey Global Institute study found that business "decisions based on data-driven insights result in 23 times greater likelihood of customer acquisition, six times greater likelihood of customer retention and 19 times greater likelihood of profitability."
BI analytics software trends
While different commentators and vendors tend to have their own lists of hot topics, here are a few you should be particularly aware of:
- Data governance has become increasingly important. The accuracy of information supplied to management has long been of concern, and data governance is now a mature discipline that can be used to improve that quality. It's important that vendors include some data governance tools as part of their BI analytics software suites.
- Self-service BI is increasingly expected, not just desired, by end users. This goes beyond the usual demand for spreadsheet support to the ability to have greater control over the nature of end-user queries. Ease-of-use is therefore an increasingly important buying criterion.
- Agile marketing continues to spread across the organizational landscape. One of agile marketing's key principles is "data over opinion," sometimes phrased as "customer data rather than the opinion of the highest-ranking person in the room." Buyers of BI analytics software should therefore place more stress than ever on the technology's ability to support rapid determination of customer responses to new products and their organization's marketing, sales and service processes.
- Experimental, or "skunkworks" groups are being set up by large enterprises to try to access public-cloud, social-media and other data for BI and other purposes. These projects tend to use Hadoop to access this data. Without oversight, these skunkworks will not mesh with the overall BI strategy of the large enterprise.
Deciding whether you need a BI analytics tool, and -- if the answer is yes -- determining which tool best meets your needs, is often a major strategic decision. However, careful assessment and comparison of vendor products, their fit with your needs and their potential for supporting new technologies in the future should make your decision relatively straightforward. To help you determine your needs, it's best to take a closer look at the many features BI analytics tools offer, as well as typical use cases for which these tools are optimized.
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