Business Analytics

Business Analytics

Business Analytics

Implementation of Business Analytics in an application is an important decision, the depth of Business analytics should be decided at the commencement of the project, and it could also be decided in the middle of the project at the end. Why it should be decided at the beginning of the project and not in the end or middle of it is, the database schema and the tables are created keeping in mind the requirements, and if the analytics requirements come later in the project it could make the relationship in DB a bit complicated.

Before we move any further it is important to describe and explain what is Business Analytics and why it is required for the people who are not well aware of this concept. Business Analytics is the study of data through mathematical analysis and formation of predictive models, it involves the investigation of historical business performance, business analytics makes extensive use of analytical modeling, and numerical analysis including predictive data modeling the results could be used by humans to make a decision or could be used by fully automated decision making. By learning from existing data, business analytics can make concrete recommendations to solve problems and improve businesses. There are different types of analytics, such as:

  • Decision Analytics: helps the users to make a decision based on the visual models, it is a systematic, quantitative, and visual approach to addressing and evaluating the important choices that businesses face, the difficulty in making the correct choice is faced by small, mid sized and large organizations while making various types of decisions, including management, operations, marketing, capital investments, or strategic choices. The decision analysis is used when the user has different options from which he can choose.
    We use Power BI’s decision tree for handling decision analytics, decision trees are used to visually represent decisions, it analyses observations from a dataset to derive conclusions about the target variables. Power BI provides visualization of decision tree charts in its visual gallery.
  • Descriptive Analytics: In descriptive analytics, an insight is gained from historical data through reporting, clustering and scoreboards, etc. to better understand what changes have been introduced in business, for example; monthly sales growth, yearly pricing changes, the total number of users or the total revenue per user/subscriber, these all describe what has occurred/changed in a business during a period.
  • Predictive Analytics: It involves the use of statistical methods and modeling techniques to get an insight into future trends/performance based on current and historical data. Predictive analytics analyze patterns in data to determine if those patterns are likely to emerge again, it allows businesses to adjust how they use their resources, and to take advantage of possible future events.
  • Prescriptive Analytics: It is related to both descriptive and predictive analysis, it relates to actionable insights and focuses on the best course of action in a given scenario when different options are available. Prescriptive analytics takes data from both descriptive and predictive sources and applies them to the process of decision-making, it can also measure the impact of a decision based on different possible future scenarios.

We use Power BI and Tableau for Business Analytics; it will be worthwhile to know what these tools are.

Power BI: It is a tool by Microsoft Corporation for Business Analytics. It is a package of software services, connectors, and apps that work together to turn unrelated sources of data into logical, visual, and interactive insights. It provides interactive visualizations and business intelligence features in a simple and interactive interface for end-users, the users can also create their reports and dashboards. Power BI provides both desktop and cloud-based services called ‘Power BI desktop’ and ‘Power BI Services’, Power BI Mobile Apps for Android and iOS devices is also available. Power Bi also allows the user to collaborate and share the reports. The users can also subscribe to the content within Power BI and they can get alerts as soon as the data changes or they can set thresholds and as soon as the threshold is reached, they receive an alert. The reports in Power BI could be Bookmarked and filtered easily. Power BI also allows users to print and export the contents. An Important part of Power Bi is the multitude of data connections handle be it an excel file or MS SQL Server, Oracle, Azure or in a service like MailChimp, Facebook or Salesforce, Power BI has built-in data, connectors that can connect with the different data sources and pull and data and store it in your dataset, once you have the dataset you can start creating visualizations that can show different portions of the data in different ways and can gain insights by creating reports.

Tableau: Tableau is another powerful data visualization tool. It helps in simplifying raw data into a very easily understandable format. Visualizations are created from the raw data and these are in the form of dashboard and worksheets like Power BI Tableau dashboards can also be customized. Tableau developer tools are used for the creation of charts, reports, dashboards, and visualization, once created these could be shared using Tableau server, Online, and Reader. Similar to Power BI the Tableau offers Tableau Desktop and Tableau Online for hosting the data on the cloud. Tableau can also pull data from different sources like excel file, pdf, Oracle, MS SQL database, Amazon web services, etc. The Tableau Desktop allows the user to code and customizes the reports, then Tableau server helps in sharing the workbooks and visualizations through Tableau Desktop application, Tableau Reader is a free tool that helps in view the content created using Tableau Desktop. Tableau Public is used to create workbooks and visualizations that are to be made public because these are stored in the Tableau’s Public cloud and don’t have any privacy, anyone can access the content, hence Tableau Public is only suited for someone who wants to make this work/data public. Below is the Tableau suit:

  • Tableau Desktop
  • Tableau Public
  • Tableau Online
  • Tableau Server
  • Tableau Reader

Tableau Server and Tableau Online can create webhook events on workbook changes, extract refreshes, and job actions, which can be sent to third-party services that support webhooks. These third-party services can use these events to perform additional actions in their service.


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