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Model Planning for Data Analytics

In this tutorial, we will talk about models for planning data analytics, where we will discuss all steps of the process one by one.

Model planning is the third phase of the lifecycle stages of data analytics. This is where the team members decide on methods, methods, and the process it plans to use in the subsequent stage of building models.

In this phase, the team focuses on the hypothesis created during discovery, when they first got familiar with data and understood the business issues or domain.

Common Tools for Model Planning Phase:

R's -

  • The main strength of the company is the ease at which high-quality plots can be created, with mathematical formulas when required.
  • The most well-known application of SQL is its base for the creation of dashboards, which are simple to build and use with the tools for reporting.
  • To build as well as interact with databases more quickly, SQL has been adapted to a range of tools, each having its own distinct markets, such as Microsoft Access and PostgreSQL.


  • It's easy to access and is able to create complex models as well as rapid analysis, and it also offers the ability to do a lot of manipulation of data.
  • The SQL monitoring of servers in the application manager is presented in a table format, which makes it simple to switch between screens of live data as well as access analytic features.
  • Data is accessible in a wide range through the user-friendly interface without having to consider the location of where it's stored.
  • Access data quickly and easily with no understanding of the data or the SQL needed to display it.
  • Enjoy seamless interfaces between loaders and users without an in-depth understanding of every loader.
  • Enhance efficiency by using basic storage options like materialistic perspectives, temporary tables, as well as partitioned tables.

Tableau Public -

  • It's a completely free program that connects any data source and connects to corporate web-based information.
  • It lets us download the file in various formats.
  • The information is available for sharing via social media.
  • This is a great source of data for anyone who wants to know the benefits of the tableau.


  • This is a programming language and programming language that allows data manipulation.
  • SAS is simple to manage and access and can be used to study information from a variety of sources.
  • SAS creates modules for social media, as well as marketing analytics, which is broadly used in the prospecting of customers.
  • It also helps forecast the behaviour of the customer and their communications.

RapidMiner -

  • It is a fully integrated system for the field of data science which can perform the analysis of predictive data.
  • It also includes advanced analytics like machine learning, data mining, and even data mining, without the requirement for programming.
  • This tool is extremely efficient and is able to produce analysis using real-time data.

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