Where does SaaS come into play?
As with other software, there is a significant amount of interest in the SaaS/cloud deployment model for BI and Analytics software. However, only a few companies have emerged that are pure-play SAAS. This is because of the complexity involved in delivering a pure SaaS BI product due to data privacy challenges, slower online response times due to data upload bottlenecks etc. Therefore, in a significant share of BI installations, data remains on-premise, even for those software vendors who focus on SaaS and cloud products.
What is BI Software?
Business intelligence software allows non-technical users access and analyze data with ease to make data-driven business decisions. Wikipedia provides a more formal definition: "Business intelligence comprise the strategies and technologies used by enterprises for the data analysis of business information."
BI software solutions are critical as companies try to expand data driven decision making across the organization. BI tools are targeted toward non-technical users and usually don’t require coding experience. Analytical training and BI knowledge and some experience with the tool is sufficient for a non-technical users to effectively use a BI tool.Business intelligence processes have two components: Data management and BI tools. Some BI vendors focus on data management. They aggregate data from different resources (e.g. internal and external) and focus on data storage, organization and cleaning. Other vendors focus on the analytical aspects of BI such as ad hoc queries, scorecards, dashboards and analysis.
What is Business Intelligence (BI)?
Business intelligence (BI) incorporates a variety of concepts to improve business decision making by using fact-based decision making. Business intelligence is the ability to collect information about the business, analyze it and react according to it.
What are BI Use Cases?
BI tools are general purpose analytical tools enabling a wide variety of functions such as reporting, data analytics, visualization, discovery, to business performance management. We can put them under 3 specific categories;
Reporting and Performance Management: Vendors in reporting space help to query data sources to produce a human-readable output, such as financial and operational data. It’s used cases include benchmarking of business processes or performance metrics to those of other companies or industries.
Data Analytics and Visualization: Discovering and communicating meaningful patterns in data and Communicating clearly and efficiently through visual means, e.g., graphics and charts with simple user experience with drag and drop features.
Complex Event Processing and Data Discovery: User driven approach to finding patterns and data points through the use of visual tools (mouse clicks: behavior of the users or maps.) and breaking down the complex processes to draw conclusions.
What are the benefits of BI?
- Single source of truth: Use of the same BI tool allows the whole company to be aligned on the key metrics with limited effort. In companies without a central BI tool, significant management and personnel time is spent aligning different departments on how to measure and track KPIs.
- Constant and effortless business monitoring: Dashboards allow all levels in the business to monitor key metrics with ease. This allows management to choose metrics to focus on and helps them align business efforts to improve these metrics.
- Data driven decision making: BI tools allow companies to make data-driven operational decisions efficiently with the help of templates and historical data. Highest level strategic decisions in most Fortune 1000 companies are driven by strategy and business teams, sometimes supported by consultants, that rely on data and insights. However, as decision importance decreases, cost of analysis to make data driven decisions increases relative to the business value generated by improved decisions. For example, a multi billion acqusition may generate multi billion benefits to the company and therefore spending $10-20m on due diligence may be worthwhile. With the same logic, selecting the exact bid price for a <$20k bid to a new customer, should only warrant an analysis cost of $100-200 at most. However, a comprehensive analysis taking into account the competition, the potential lifetime value of time customer, cost to serve the customer etc. would cost a lot more than $100-200 if completed ad-hoc with no specialized tools. BI tools dramatically reduce the cost of such analysis by providing easy access to historical data, analytical functions and enabling collaboration via templates. Therefore, BI tools ensure that even operational decisions are data driven.