As business intelligence and information analysis play an important role in the activities of all kinds of organizations, knowing how to use the power of data analysis tools has become a competitive achievement.
The primary responsibility for managing and extracting intelligence from business data usually rests with dedicated professionals such as data scientists and large data engineers. But these statistics should be accessible and meaningful to other partners in the company who have no technical background.
In this article, we’ve compiled the best and most popular data analytics tools to consider in 2020 – it covers a wide range of application situations, and includes applications across organizations of all sizes. These data analytics tools range from generic to fully serviced business packages.
Do you want to become a Data Science Expert join the Live Training Program on Naresh I Technologies.
R, Python
- R and Python are the best programming languages used in the field of data analytics.
- R is an open source tool used for statistics and analytics.
- Python is advanced, with easy syntax and dynamic meaning
Microsoft Excel
- Microsoft Excel is a platform that helps you get better statistics about your data.
- As a member of the most famous tools for data analytics, Microsoft Excel offers users with features such as sharing workbooks,
- working with the latest version for live collaboration, and adding Excel data directly from a photo.
Tableau
- A market-leading data analytics tool used to analyze and visualize data, Gartner named Magic Quadrant 2020 a leader for the eighth year in a row.
- Empanel for ease of use allows table users to work on live data-packages and spend more time analyzing data rather than ranking data.
- The product list family includes Tableau Desktop, Tableau Server, Tableau Online, Tableau Reader .
RapidMiner
- The Rapidminer Data Analytics tool makes it easy for non-programmers and researchers to analyze information quickly, to define and create processes, and to import, analyze, and create predictive models of the data in them.
- The 2020 Gartner Magic Quadrant for Data Science and Machine Learning Platforms is compatible with web applications such as Flask and Node JS, as well as compatible with mobile platforms such as Android and iOS for importing and importing fast minor machine learning models.
- It allows users to synchronize the entire spectrum of the big data analysis life cycle.
KNIME
- KNIME or Konstanz Information Miner is a free and open source data analysis, reporting and integration tool.
- Allows KNIME users to create workflows, sample at each stage of analysis, manage data flow, and update their tasks with over 2000 analytics browsers.
- No programming knowledge is required before using KNIME as a data analytics tool to gain intelligence.
- The product integrates tools from different regions into KNIM’s own nodes into a single workflow, integrating script into connectors for machine learning, Python or R, or Apache Spark.
Power BI
- Power BI is Microsoft’s business analysis product.
- Its data analysis tool collection includes a number of products, including Power BI Desktop, Power BI Pro, Power BI Premium, Power BI Mobile, Power BI Embedded, and Power BI Report Server.
- In addition, Power BI has recently introduced a number of solutions, including Azure + PowerBI and Office 365 + PowerBI, which allow users to analyze their data, link information, and secure data across various office platforms.
Apache Spark
- One of the most successful projects of the Apache Software Foundation is the open source cluster system architecture Apache Spark, which performs live data processing.
- Currently, in version 2.4.6, the latest iteration (version 3.0.0) is in preview.
- If you need big data analysis on a budget, Apache Spark is definitely something to consider.
- Spark’s machine speed and scaling data make it a very popular data analytics tool among scientists.
- In addition to its core analytics functionality, Apache Spark can be used for a variety of functions, including cleaning and modifying data, creating models for evaluation and scoring, and setting up data science tubes for production.
Qlik
- Qlik is a self-service business intelligence, data visualization, and data analytics tool that aims to accelerate business value through data by providing features such as data integration, data literacy, and data analysis.
- Gartner Magic Quadrant 2020 for Analytics and PI Platforms has chosen the site as a leader.
- Qlik integrates various products and services for data integration, data analytics and developer platforms. Some are available during the 30-day trial period.
Talend
- Developed in the Eclipse graphical development environment, Talend is one of the most powerful data integration ETL (Export Transform Load) tools available on the market.
- ETL allows talent users to easily manage all the activities involved in the process, and aims to provide consistent, accessible, and clean data to all.
Splunk
- Named after Gartner’s vision of the 2020 Magic Quadrant for ABM, Slunk is a data analytics tool for searching, analyzing, and visualizing machine-generated data collected from applications, websites, and other sources.
- The brand has developed products in various fields such as IT, Security, Devops and Analytics.
- Splunk can handle small, medium and large business enterprise data, public administrations and non-profit organizations.
- Data Integration Tools and Data Quality Tools has been selected as the 2019 leader in Gartner’s Magic Quadrant.
Do you want to become a Data Science Expert join the Live Training Program on Naresh I Technologies.
