Many analytical tools for data analysis can help you extract data insights from the pool of data. Start your bright and shining career with our Data Analytics Course. Get 100% placement assistance and certification after completion of the course. Read the article to learn about some of the best data analytical tools.
What is Data Analytics?
Data Analytics is the process of analyzing raw data to extract meaningful insights and trends, which can then be used to make information decisions and drive business strategy. It involves various processes and technologies to process, clean, interpret, and visualize data to uncover patterns, correlations, and other valuable information.Â
Analytical tools for Data Analytics: TypesÂ
Data Analytics can be broadly classified into several types based on the objectives, methodologies, and nature of the data being analyzed. The different types are not mutually exclusive and can be used in combination to gain deeper insights and drive more information decision-making.Â
Depending on the specific goals and requirements of a project or organization, different types of data analytics are defined, which include:
- Descriptive Analytics: Descriptive analysis focuses on summarizing historical data to understand what has happened in the past. It involves basic statistical analysis, such as calculating averages, counts, frequencies, and other summary measures to describe the characteristics of the data.
- Predictive Analysis: Predictive analysis uses historical data to predict future outcomes or trends. It involves building statistical models and machine learning algorithms to forecast future behavior, such as customer churn, sales trends, or stock prices, based on past patterns and relationships in the data.
- Diagnostic Analytics: Diagnostic analytics seeks to determine the causes of prior events or outcomes. It involves deeper analysis to uncover patterns, trends, and correlations in the data, often using techniques like data mining and root cause analysis to understand why certain events occurred.
- Prescriptive Analysis: Prescriptive analytics goes beyond predicting future outcomes to recommend actions or decisions to optimize future outcomes. It involves leveraging advanced analytical techniques, optimization algorithms, and decision models to determine the best course of action given specific objectives, constraints, and uncertainties.
- Big Data Analytics: Big data analytics involves analyzing large volumes of structured and unstructured data to extract insights and value. It often requires specialized tools and techniques to process, store, and analyze massive datasets, such as those generated by social media, sensors, and other sources of big data.
- Real-time Analytics: Real-time analytics involves analyzing data as it is generated or collected in real-time, enabling organizations to make immediate decisions or take timely actions based on up-to-date information. It is commonly used in applications like fraud detection, monitoring systems, and recommendation engines.
Top 11 Best Analytical Tools for Data Analysis in 2024
Some best analytical tools for data analysis are mentioned below. Know their benefits, features, and descriptions in the table below.
1. Microsoft Power BIÂ
Microsoft Power BI is a powerful business analytics tool developed by Microsoft. It allows users to visualize and analyze data from various sources to gain insights and make data-driven decisions.Â
| Analytical Tools for Data Analytics: Microsoft Power BIÂ | |
| Feature | Description |
| Data Connectivity | Connects to various data sources, including databases, spreadsheets, cloud services (Azure, Google Analytics), and online services. Supports both cloud and on-premises data. |
| Data Analysis | Offers statistical functions, forecasting, clustering, and time-series analysis. Allows users to create custom calculations, measures, and tables for insights. |
| Data Visualization | Rich set of visualization options including charts, graphs, maps, and tables. Supports customization, interactivity, and creation of dashboards for monitoring key metrics. |
| Data Exploration | Interactive data exploration through drill-downs, filters, and slicing/dicing. Supports natural language queries for asking questions and receiving answers. |
| Security and Governance | Robust security features include role-based access control, encryption, and data loss prevention. Provides auditing and compliance capabilities for sensitive data. |
2. Tableau
Tableau is a powerful data visualization software that allows users to create interactive and shareable dashboards, reports, and visualizations from various data sources.Â
| Analytical Tools for Data Analytics: Tableau | |
| Feature | Description |
| Data Connectivity | Tableau supports connectivity to various data sources, including databases (SQL Server, Oracle, MySQL, etc.), spreadsheets (Excel, CSV), cloud services (Amazon Redshift, Google BigQuery), and web data connectors. |
| Visualization Types | Tableau offers a wide range of visualization types, such as bar charts, line charts, scatter plots, heat maps, geographic maps, pie charts, histograms, and more. |
| Ad Hoc Analysis | Tableau enables ad hoc analysis through drag-and-drop gestures, filters, and calculations, allowing users to quickly explore and manipulate data to uncover insights. |
| Advanced Analytics | Tableau supports advanced analytics capabilities, including predictive analytics and statistical modeling, through integrations with R, Python, and other statistical tools. |
| Collaboration & Sharing | Users can publish their Tableau workbooks to Tableau Server or Tableau Online for sharing with others within the organization or externally. Workbooks can be accessed and interacted with by authorized users. |
| Security | Tableau offers robust security features to control access to data and content, including user authentication, permissions management, encryption, and data governance capabilities. |
3. Qlik Sense
Qlik Sense is a modern, self-service data analytics and visualization platform developed by Qlik. Qlik Sense is a versatile and powerful data analytics platform that empowers users to explore data and create compelling visualizations.
| Analytical Tools for Data Analytics: Qlik Sense | |
| Feature | Description |
| Associative Data Model | It enables users to explore data relationships freely without predefined paths or queries. |
| Data Connectivity | Supports connectivity to various data sources, including databases, spreadsheets, cloud services, and web data connectors. |
| Self-Service Visualization | Offers an easy-to-use interface for building interactive visualizations and dashboards. |
| Smart Search | Features a powerful search engine for quick exploration of data using natural language queries. |
| Collaboration & Sharing | Allows users to publish apps, share insights, and collaborate with others within the organization. |
| Advanced Analytics | Supports predictive analytics and statistical modeling through integrations with R and Python. |
| Mobile Accessibility | Provides access to apps and visualizations on mobile devices through the Qlik Sense Mobile app. |
4. LookerÂ
Looker is an analytical platform that was acquired by Google Cloud in 2020. Looker is a business intelligence platform. It helps to explore, analyze, and visualize the data to gain actionable insights.Â
| Analytical Tools for Data Analytics: Looker by Google Cloud | |
| Feature | Description |
| Data Exploration | Explore and query data from multiple sources with an intuitive interface. |
| Visualization & Dashboards | Create interactive and insightful visualizations and customizable dashboards. |
| Data Modeling | Define reusable data models and business logic for consistency in reporting and analysis. |
| Embedded Analytics | Integrate data-driven insights directly into applications, websites, and workflows. |
| Collaboration & Sharing | Share reports, dashboards, and analyses with colleagues and stakeholders for collaboration. |
| Data Governance & Security | Ensure data confidentiality, integrity, and availability with granular access controls and encryption. |
| Scalability & Performance | Scale to handle large volumes of data and complex analytical workloads with high performance. |
| Integration | Seamlessly integrate with Google Cloud services like BigQuery and Google Analytics for comprehensive analytics solutions. |
5. Klipfolio
Klipfolio is a cloud-based business intelligence and dashboard software that enables organizations to create, organize, and share interactive dashboards and reports to monitor key performance indicators (KPIs) and track business metrics in real life.
| KlipFolio | |
| Feature | Description |
| Dashboard Creation | Klipfolio allows users to create customized dashboards by assembling visualizations (klips) from various data sources. |
| Data Connectivity | Klipfolio supports connectivity to a wide range of data sources, including databases, spreadsheets, cloud services, and web APIs. |
| Visualization Types | Klipfolio offers a variety of visualization types, such as charts, gauges, tables, maps, and text components, to represent data effectively. |
| KPI Monitoring | Users can track key performance indicators (KPIs) in real-time and set thresholds or alerts to monitor performance against goals. |
| Sharing and Collaboration | Klipfolio allows users to share dashboards and reports with colleagues and stakeholders, and collaborate on data analysis and decision-making. |
| Security | Klipfolio offers security features such as role-based access control, SSL encryption, and data privacy controls to protect sensitive information. |
| Integration | Klipfolio integrates with various third-party applications and services, including CRM systems, marketing platforms, and cloud storage solutions. |
6. Zoho AnalyticsÂ
Zoho Analytics is a business intelligence and analytical platform developed by Zoho Corporation. Formerly known as Zoho Reports. Zoho Analytics provides a comprehensive solution for businesses looking to analyze and derive insights from their data.Â
| Analytical Tools for Data Analytics: Zoho Analytics | |
| Feature | Description |
| Data Connectivity | Zoho Analytics supports connectivity to various data sources, including databases, cloud storage, business applications, and third-party services. |
| Ad Hoc Analysis | Users can perform ad hoc analysis by exploring and manipulating data using drag-and-drop tools, filters, and calculations. |
| Security | Zoho Analytics includes security features such as role-based access control, data encryption, and audit logs to ensure data confidentiality and integrity. |
| Scalability & Performance | Zoho Analytics is scalable and capable of handling large volumes of data, with features for optimizing performance and managing resources efficiently. |
| Integration | Zoho Analytics integrates with a variety of third-party applications and services, including CRM systems, marketing automation tools, and cloud platforms. |
7. Domo
Domo is a cloud-based platform that offers a suite of business intelligence and data analytics tools. It is designed to provide a centralized platform for managing and analyzing data, with a focus on ease of use and accessibility for non-technical users.
| Analytical Tools for Data Analytics: Domo | |
| Feature | Description |
| Data Integration | Domo provides robust data integration capabilities, allowing users to connect to various data sources, including databases, cloud applications, spreadsheets, and more. |
| Collaboration | Domo facilitates collaboration through features like sharing, commenting, and annotation, enabling teams to work together and make data-driven decisions. |
| Predictive Analytics | Domo offers predictive analytics capabilities to forecast trends, identify patterns, and make data-driven predictions using machine learning algorithms. |
| Scalability & Security | Domo is built to scale with the needs of growing organizations and offers enterprise-grade security features, including encryption, authentication, and data masking. |
8. SisenseÂ
Sisense is a business intelligence software platform that enables organizations to analyse and visualize complex datasets to uncover actionable insights and data-driven decisions.
| Sisense | |
| Feature | Description |
| Data Connectivity | Connects to various data sources including databases, spreadsheets, etc. |
| Visual Analytics | Creates interactive dashboards, reports, and visualizations. |
| Embedded Analytics | Integrates analytics directly into applications and workflows. |
| Collaboration | Enables sharing, commenting, and collaboration on insights. |
| Scalability | Scales to handle large volumes of data and users. |
| Security | Provides enterprise-grade security features for data protection. |
9. Google AnalyticsÂ
Google Analytics is a web analytics service offered by Google that tracks and reports website traffic. It is widely used by website owners, marketers, and businesses of all sizes to monitor website performance.Â
| Analytical Tools for Data Analytics: Google Analytics | |
| Feature | Description |
| Traffic Analysis | Tracks website metrics like visitors, page views, and session duration. |
| Audience Insights | Provides demographic data such as age, gender, and interests of visitors. |
| Traffic Sources | Identifies the sources of website traffic, such as search engines and referrals. |
| Goal Tracking | Sets and tracks specific goals or conversions, like form submissions or purchases. |
| E-commerce Tracking | Measures sales performance for e-commerce websites, including revenue and products sold. |
10. SAP Analytics CloudÂ
(SAC) is a cloud-based analytics platform developed by SAP that combines business intelligence, augmented analytics, and planning capabilities in a single solution.Â
| Analytical tools for data analytics: SAP Analytics Cloud (SAC) | |
| Feature | Description |
| Data Connectivity | Connects to various data sources including SAP systems, databases, and cloud platforms. |
| Visual Analytics | Creates interactive dashboards and visualizations. |
| Planning | Supports financial planning, budgeting, and forecasting. |
| Predictive Analytics | Offers predictive modeling and trend analysis. |
| Collaboration | Enables sharing and collaboration on data analysis. |
| Mobile Accessibility | Accessible on mobile devices for on-the-go analysis. |
| Governance | Provides security features for data protection. |
| Scalability | Scales to handle large volumes of data and users. |
11. KnimeÂ
Knime is a free and open-source data analytic tool used to perform data analytics and reporting. It can easily integrate machine learning models and data mining.
Analytical Tools for Data Analytic FAQs
What are data analytical tools?
Data analytics tools are technologies that help to collect, interpret and display important insights derived from data.
Which is the best data analytical tool?
Some of the major data analytical tools are Tableau, Looker, Zoho Analytics, Sisense, Google Analytics, Knime, etc.
Is SQL a data analysis tool?
SQL is a procedural programming language used for accessing, processing, cleaning, and analysing databases. It is easy to learn and demanded by major companies.
