Top 10 Data Analytics Tools: Empowering Data Analysts in 2020

by Waseem from Techal

In today’s data-driven world, where an astonishing 2.5 quintillion bytes of data are generated daily, data plays a crucial role in decision-making for businesses. To gather insights from this vast amount of data, data analysts rely on various tools. In this article, we will explore the top 10 data analytics tools that every skilled data analyst must learn in 2020.

Plonk: Unleash the Power of Machine-Generated Data

Splunk is a platform renowned for its ability to search, analyze, and visualize machine-generated data from various applications and websites. Trusted by organizations like Domino’s, Lenovo, and Intel, Splunk offers three products: Splunk Free, Splunk Enterprise, and Splunk Cloud. These products differ in their features and can be downloaded for free or used through a trial version. Splunk aims to bring data to every part of your organization, helping teams prevent, predict, and solve problems by providing clear visibility and streamlining security processes.

Talent: Streamline the ETL Process

Talend is a powerful data integration and ETL (Extract, Transform, Load) tool that simplifies the management of data integration steps. It offers five products, including Talend Open Studio, Talend Pipeline Designer, and Talend Cloud Data Integration. Trusted by companies like Aldo, AB InBev, and Euronext, Talend ensures clean, accessible, and compliant data for critical decision-making.

QlikView: Accelerate Business Value Through Data

QlikView is a self-service business intelligence, data visualization, and analytics tool. It provides features such as data integration, data literacy, and data analytics. With a free trial period of 30 days, QlikView is trusted by over 50,000 customers worldwide, including Cisco, Samsung, and NHS. Recently, QlikView introduced Quick Alerting, an intelligent platform that helps organizations handle exceptions, notify users of potential issues, and prompt actions based on derived insights.

Apache Spark: Real-Time Processing Made Easy

Apache Spark is a leading open-source cluster computing framework used for real-time data processing. Companies like Oracle, Verizon, and Visa rely on Apache Spark for its ease of use and speed. Spark offers high-level APIs in Java, Scala, Python, and R, making it convenient for big data processing. Its machine learning library further enhances its capabilities.

Power BI: Microsoft’s Business Analytics Solution

Power BI is a Microsoft product widely used for business analytics. Offering interactive visualizations and self-service business intelligence capabilities, Power BI allows end users to create dashboards and reports independently. Companies like Adobe, GE Healthcare, and Heathrow use Power BI to analyze data and achieve powerful results. Power BI is continuously evolving, with recent solutions like Azure + Power BI and Office 365 + Power BI enabling seamless data analysis, connection, and protection across platforms.

Knime: Open-Source Data Analytics Made Easy

Known as the “9s”, Knime (short for 9 Constants Information Miner) is a free and open-source data analytics, reporting, and integration platform. It offers two software solutions: Knime Analytics Platform and Knime Server. Knime Analytics Platform enables users to clean and gather data, create reusable components, and build data science workflows. Knime Server provides enterprise-level features for workflow deployment, team collaboration, management, and automation. Knime has been adopted by companies like Siemens, Novartis, and Continental, empowering them with meaningful insights.

RapidMiner: Data Science and Machine Learning Made Efficient

RapidMiner, named a visionary by Gartner, is a platform for building data processes, creating machine learning models, and deploying them. BMW, Hewlett Packard Enterprise, and Sanofi rely on RapidMiner for their data processing and machine learning needs. RapidMiner 9.6, the latest release, extends the platform to full-time coders and business intelligence users, providing a fully transparent end-to-end data science experience.

Tableau: Simplify Data Analysis and Visualization

Tableau is a market-leading business intelligence tool that simplifies data analysis and visualization. Trusted by organizations like Citibank, Deloitte, and Skype, Tableau allows users to work with live datasets and spend more time on analysis rather than data manipulation. With products like Tableau Desktop, Tableau Server, and Tableau Public, Tableau offers fast analytics, smart dashboards, and seamless sharing across web and mobile devices.

Microsoft Excel: The Timeless Classic

Microsoft Excel remains one of the most popular tools for data analytics. It provides features such as real-time collaboration, photo-based data entry, and sharing workbooks. Used by organizations like McDonald’s, Marriott, and IKEA, Excel allows users to gather meaningful insights from their data. Recent advancements in Excel include workbook statistics, high-quality stock images, and enhanced Windows platform integration.

R and Python: The Powerhouse Programming Duo

R and Python are the top programming languages used in the data analytics field. R is an open-source tool for statistics and analytics, while Python is a high-level interpreted language with easy syntax and dynamic semantics. ANZ, Google, YouTube, and Netflix are just a few of the many companies leveraging R and Python for data analysis. With frequent updates and enhanced features, both languages continue to improve the data analysis process.

FAQs

• Q: What is the pricing for these data analytics tools?

• A: Each tool has its pricing options, which may vary based on features and functionality. It is best to visit the official websites of the respective tools for detailed pricing information.

• Q: Can I try these tools before purchasing them?

• A: Yes, most of these tools offer free trial versions or community editions that allow users to explore their features before making a purchase decision.

• Q: Are these tools suitable for both small startups and large enterprises?

• A: Yes, these tools cater to a wide range of organizations, from small startups to multinational companies. They offer scalable solutions to meet the unique needs of businesses of all sizes.

• Q: How can I learn these data analytics tools?

• A: Many of these tools provide online training programs and certification courses. Refer to the official websites or online learning platforms for more information on training opportunities.

Conclusion

Data analytics tools are essential for data analysts to gather insights and make informed decisions. From Splunk’s powerful data search and analysis capabilities to Microsoft Excel’s versatile data processing features, each tool brings its own unique strengths. Whether you are a data analyst, a technology enthusiast, or a technology engineer, understanding and mastering these tools will empower you with the knowledge to navigate the ever-evolving world of data analytics.

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Thank you and happy data analyzing!