Intelligence In Business – The information technology (IT) market is full of many buzzwords and terms that are often used interchangeably. However, in some cases, there are subtle differences between terms that are important to understand and that can affect the choice of tools and how to deploy them. An example is the use of the terms business intelligence vs. business analytics or BI vs. BA. Read on to learn how these terms and tools differ and how they complement each other.
Although there were some earlier uses, business intelligence (BI) as it is understood today evolved from the decision support systems (DSS) used from the 1960s to the mid-1980s. Then, in 1989, Howard Dresner (former Gartner analyst) proposed “business intelligence” as a general term to describe “concepts and methods for improving business decision-making using event-based support systems.”
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The most modern definition provided by Wikipedia describes BI as “a set of strategies and technologies used by businesses to analyze business intelligence data.” Another definition offered by TechTarget states that “Business intelligence (BI) is a technology-based process for analyzing data and providing actionable information that helps executives, managers, and employees make informed business decisions.”
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TechTarget’s definition goes on to describe how, as part of the BI process, organizations collect data from internal IT systems and external sources, prepare it for analysis, run queries against the data, and create data visualizations, BI dashboards, and reports for presentation data and make the results of analytics available to business users for business decision making and strategic planning.
“Business analytics” or “data analytics” is the more modern term applied to the broader field of BI, corporate performance management (CPM), and analytical tools and applications. What I like about the term analytics is that it suggests a more “active” approach to information consumption. Where BI is often seen primarily as the process of collecting information and formatting it for delivery to end users – analytics is more about the process of accessing, processing, consuming, manipulating, slicing, slicing and drilling into information to understand trends and get answers to detailed questions.
Below is the International Data Corporation (IDC) Taxonomy (see figure 1) for Big Data and Analytics Software, which illustrates how all these tools and applications fit together. There are three main market segments in this classification:
With the IDC classification identifying the different types of business analytics tools available in the market, let’s talk about the use cases for business analytics. There are essentially three types of analytics that businesses use to drive their decision making:
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They make up the majority of today’s management reports. It is the analysis of historical data using simple techniques such as data aggregation and data mining, which are used to uncover trends, signals and patterns. This information is provided to end users through reports and management dashboards that include visual data representations such as line charts, bar charts, and pie charts that provide actionable insights and provide the basis for additional analysis of the underlying details.
Is a more advanced method of data analysis that applies statistical analysis and machine learning techniques to historical data to project future outcomes and the likelihood of those outcomes. Use cases for predictive analytics include problems such as demand or sales forecasting, fraud detection, and customer churn analysis.
, prescriptive analysis takes the process one step further by showing decision makers which future scenario is the best way forward using a variety of statistical methods. This is achieved by collecting data from a range of descriptive and predictive sources and applying it to the decision-making process. It allows teams to see the best course of action before making decisions, saving time and money while achieving optimal results.
OneStream empowers Finance teams to lead with speed by integrating predictive analytics with core CPM processes: planning, budgeting and forecasting. financial consolidation; reporting; and the quality of financial data. And with our integrated predictive analytics solution (see figure 2), OneStream unleashes Finance transformation to take budgeting, planning and forecasting processes even further – enabling teams to plan, analyze and forecast with confidence.
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As announced at OneStream’s 2021 Splash Virtual event, OneStream’s AI Services and Sensible ML solution will enable finance teams to leverage predictive ML models without extensive data scientist work. This solution will take users through a step-by-step process for each part of the ML model creation and development process. Including feature engineering through configuration, training and development of advanced algorithms.
Business Intelligence tools are part of a broader range of business analytics tools that includes analytics infrastructure, CPM and analytics applications, as well as advanced predictive analytics tools. These business analytics tools and applications are all designed to help organizations collect, organize, and disseminate information to executives and decision makers, and provide the “analytical intelligence” needed to make timely, informed decisions that can drive in improved business performance.
To learn more about OneStream’s approach to predictive analytics and machine learning, download our white paper and contact OneStream if your organization is ready to transform Finance by aligning advanced predictive analytics and machine learning with the basic CPM processes.
Please switch to the latest version of a modern web browser such as Chrome, Firefox or Edge to access our website. Business intelligence is a broad term that encompasses all the tools and practices used to collect, structure, analyze and transform raw data into actionable business insights. BI deals with methods and tools for transforming unstructured data sets and compiling them into understandable reports or dashboards of information. Most BI analysts and organizations require BI tools to stay ahead of competitors and optimize overall performance. The ultimate goal of BI is to continuously monitor business performance to ensure that an organization remains on track to achieve its strategic goals. It allows decision makers to make course corrections if necessary.
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Your data source channels can be: • Data from stakeholders • Data from industry-wide analytics • Information from your employees and departments • Google Analytics, CRM, ERP
As part of launching your company’s business intelligence strategy. Together with your team, we’ll help you design a custom-designed dashboard to analyze data from key data sets to improve business decisions. With the application in modern BI, you will be able to visualize and analyze your data through a screen of the status of key performance indicators (KPIs) and other important business metrics and data points for an organization, department, team or process.
Multiple data visualizations are generally included in BI dashboards to provide business users with a consolidated view of key KPIs and trends for both decision making and strategy. They are more interactive than static reports, allowing users to drill down into the data behind the charts and visualizations for deeper analysis.
It is possible to create realistic, accurate performance numbers for your business by combining KPIs and Business Intelligence (BI). This eliminates the need for project managers and department heads to manually analyze company performance and adjust KPIs on a regular basis. KPIs generated by BI also lead to a more efficient business process.
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Business intelligence software and programs are differentiated by the level of flexibility it gives users to interact with data or how it helps provide insights into new business questions or monitor ongoing processes.
Choosing which program to use depends on your organizational requirements, data types, budget, and goals. So here are the key features and benefits of Tableau & Cognos & Power BI.
Power BI is the general term for a collection of cloud-based applications and services that enable businesses to collect, manage and analyze data from a range of sources using a simple user interface.
Power BI is a business intelligence tool that can be used for many purposes. It allows your business to visualize its data and share information. This solution helps your business handle data from different sources and provides visualization after the cleansing and integration process. It also offers an Ad-hoc reporting facility which helps in analyzing the data.
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The Power BI tool can also be customized to help your business transform data from its various data sources into interactive BI dashboards and reports. It also provides multiple software connections and services.
Power BI works with seemingly all of your business data, so any area your business wants to report on will use all the data available.
Ad-hoc analysis is any business reporting or data analysis that is curated and created by users as and when they need it. Ad-hoc analysis in business intelligence stands in stark contrast to the managed reports seen in the early days of business analysis, which were based on templates distributed by IT departments.
An ad-hoc analysis allows the user to specify which data sources to draw from and how to present that data. A key differentiator of ad-hoc analytics is its ability to deliver fully customized analytics.
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For this reason, ad-hoc analysis can run the gamut from a simple one-off data table to the intricate detail of sales reporting using dashboards, interactive maps, and other advanced visualization features.
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