5 Top Business Intelligence Tools
Business intelligence is valuable, timely, accurate, high-value, and actionable business insights, and the work processes and technologies used to obtain them. Business intelligence technologies transform raw data into meaningful and useful information for business purposes. Common functions of business intelligence technologies are reporting, online analytical processing, analytics, data mining, complex event processing, business performance management, benchmarking etc.
Important BI implementation challenges are –
1) Resistance to BI adaption – A BI initiative can change the way in which business users do their data analysis. It might also entail changes to the procedures in place at the organization. Thus a BI deployment can face resistance from business users as well as various IT teams. Building strong relationships within IT and data management teams is necessary to counter this challenge. Also required is full backing of the top management to drive adaption of BI and new reporting standards in the organization. A company can also form central BI committee or center of excellence to drive BI initiatives.
2) Data volatility – Data sources, downstream application or the process can change while a large scale BI implementation is still going on. Planning in advance for data volatility by maintaining data hierarchies and relationships is crucial to counter this. Also it will be helpful if BI implementation plan is integrated with other project plans.
3) Functionality limitation – It is highly important to be aware of your BI requirements and communicate them to the vendors in clear terms. Various BI products available should be thoroughly studied and checked against requirements before doing selection. In depth study must be carried out even while selecting the vendor. The ability of the vendor to execute the project, availability of skills, vendor track record are some of the points one should check.
4) BI penetration – Even if BI is implemented it is of no help if people are not using it. Getting more and more employees to make used of BI functionalities is necessary to the success of BI program. Thus getting the used involved well in advance before BI implementation begins and providing them with proper training is a must.
5) Clean data – Data quality is a severe challenge faced during BI implementation. Different source systems have varying layers of controls and business-rule consistency. Many a times data in different sources are in different formats. Correcting the data at the source and modifying the procedures is required to counter this.
6) Scope creep - BI projects have a notoriously high incidence of scope creep because BI covers many departments and often touches many different preexisting systems. This can be countered by employing good business analyst who can provide excellent business requirements, by building flexibility into the project plan and by adhering to strict change management processes.
Business intelligence has been used to identify cost-cutting ideas, uncover business opportunities, roll ERP data into accessible reports, react quickly to retail demand and optimize prices. BI software can give companies more leverage during negotiations by making it easier to quantify the value of relationships with suppliers and customers.
Value-based reimbursement models are rapidly changing the face of healthcare. To compete in the new era of patient-centered medical homes, accountable care organizations and initiatives related to reducing the cost of care, hospitals of all sizes need business intelligence (BI). Hospitals increasingly are expected to measure, report on, and manage a wide variety of operational, financial and clinical indicators. Ultimately, reimbursement is at stake, with incentives handed to hospitals whose data shows lower costs and better patient care—and penalties assessed on those whose data falls short.
2. Retail Shops
There are intelligent retailers such as Wal-Mart and Tesco are heavy users of BI. Take Tesco, for example, who has become the second most powerful retailer on the planet. This has not happened by chance but through applying the principles of an intelligent company. Tesco have identified two factors above all: making sure everyone in the company is actively engaged in trying to improve performance – all the time; and having the data and analytical skills to test ideas and turn insights into customer and business relevant actions.
Restaurant chains such as McDonalds, CKE and T.G.I. Friday’s have successfully applied the principles of an intelligent company. They use BI to make strategic decisions, such as what new dishes to add to or remove from their menus and which underperforming stores to close. They also use BI for tactical matters such as renegotiating contracts with suppliers and identifying opportunities to improve inefficient processes.
Yahoo Inc. is another company that used BI effectively to improve their website. The organization receives many millions of hits to its home page each hour. To test alteration to the home page they randomly assign one or two hundred thousand users to an experimental group and have several million other visitors as a control group. By doing so, they can quickly see whether or not the alterations to the home page leads to the assumed change in the behavior of the customer. This in turn allows them to optimize their offerings to enhance revenues and profits. The results of these experiments can often be seen within minutes through BI, and Yahoo! typically runs about 20 experiments at any given time.
Few of the to tools from top companies are:
1) IBM Cognos BI 10.2, Cognos Insight, SPSS Modeler 15, Analytical Decision Management 7.0 and Analytic Answers are some of the major BI products by IBM
2) IBM Cognos Express 10.1, provides comprehensive BI suite functionality at a lower license cost. This is ideal for departmental, workgroup or smaller company business analytics requirements.
3) Analytic Answers is a cloud based IBM product which offers analytics-as-a-service. You simply use a web browser to upload sets of data and download results which are expressed in terms that can be acted on promptly.
4) IBM products are chosen for the comprehensive functionality and ability to integrate easily with information infrastructure i.e. databases and servers.
5) IBM Cognos products are difficult to use as compared to its competitors and they are mainly used for creating static reports.
1) SAP BI suite consists of products such as SAP BO Business Intelligence 4.0, SAP crystal reports for enterprise reporting, Dashboard Design tool, SAP BO Explorer for self service BI, SAP Lumira Cloud for sharing self service analytics etc.
2) Most of the major system integrators all have large SAP and BusinessObjects practices. Access to people (internal or external) who know SAP BW or BusinessObjects is rarely difficult.
3) SAP offers an integrated mobile BI toolkit so that developers can leverage the SAP Mobile Platform for mobile analytics app design, device management and device security.
4) SAP Predictive Analysis integrates analytical capabilities with the real-time and in-memory processing. Its advanced analytics products can be used for uses cases such as Customer Segmentation Accelerator, and Business Planning and Consolidation.
1) Oracle Business Intelligence Enterprise Edition (OBIEE) is well suited for building large, IT-managed and centrally governed global deployments.
2) Oracle products are chosen because of ease of integration optimization with broader oracle stack. Oracle BI offers more than 80 prebuilt analytic applications for other enterprise applications such as Peoplesoft, Siebel etc.
3) Oracle’s newest engineered system, Exalytics In-Memory Machine, provides an optimized hardware and software configuration designed for large and complex analytics workloads, including dynamic planning and what-if and scenario analysis.
4) OBIEE is primarily used for systems of record, static and parameterized reporting, as well as dashboards centrally developed by IT and delivered to report consumers.
1) The company’s strategy has been to enhance the BI capabilities in three of its core offerings — including Microsoft Office (specifically Excel), Microsoft SQL Server and Microsoft SharePoint
2) Microsoft’s products are driven by its IT-oriented BI authoring tools within SQL Server, which are based on Visual Studio, the broadly adopted development environment.
3) By incorporating BI capabilities into its most ubiquitous products, and by removing deployment barriers, Microsoft virtually guarantees its BI offering’s continued and even expanded adoption, particularly in organizations that have standardized on Microsoft for information management.
4) Because Microsoft’s BI platform capabilities exist across three different tools (Office, SQL Server and SharePoint) that also perform non-BI functions. Thus it puts more burden on customers to integrate necessary components, compared with the all-in-one purpose-built BI platforms offered by most other vendors in the BI market.
5) Microsoft lags behind most other BI vendors in delivering mobile BI capabilities. It has been slow to deliver BI on mobile devices.
1) SAS’s portfolio includes tools in areas such as BI, performance management, data warehousing and data quality; however, unlike most other BI platform vendors, SAS primarily focuses on advanced analytical techniques, such as data mining and predictive modeling.
2) SAS’s products are used for large datasets and to perform analysis with above-average complexity. They are difficult to use as well.
3) Visual Analytics, is its product that merges dashboard design with diagnostic analytics and the use of predictive models.
4) SAS is a dominant company in predictive analytics category. Its dominance is challenged mainly by IBM through SPSS predictive analytics.
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