Essential Tools for Data Analysis
Data analysis is a crucial field in today’s digital landscape, utilized across various industries. Below are some of the most important tools employed for data analysis:
Microsoft Power BI
Microsoft Power BI serves as a professional information platform that accommodates numerous data sources, enabling users to create and share reports and dashboards. Users can seamlessly integrate multiple dashboards and reports within the Power BI application for straightforward distribution.
SAP BusinessObjects
SAP BusinessObjects provides a suite of business intelligence applications designed for data exploration, analysis, and reporting. Targeted towards less technical business users, the tool is capable of complex analyses. It also integrates well with Microsoft Office products, facilitating quick transitions between applications such as Excel reports and business applications while allowing for self-service predictive analytics.
Sisense
Sisense is a data analytics platform aimed at assisting both technical developers and business analysts in managing their business data. It features a comprehensive range of drag-and-drop tools and offers interactive dashboards for collaboration. A unique aspect of Sisense is its proprietary “In-Chip” technology, which enhances computation by utilizing CPU caching rather than relying on slower RAM.
TIBCO Spotfire
TIBCO Spotfire is a data analysis platform that offers natural language search capabilities and AI-driven data insights. As a comprehensive visualization tool, it can deploy reports for both mobile and desktop applications. Spotfire includes click-and-point tools for building predictive analytics models.
ThoughtSpot
ThoughtSpot is an analytics platform that enables users to investigate data from various sources through reports and natural language search queries. Its AI system, SpotIQ, uncovers insights to help users identify patterns they might not have thought to search for. The platform also automates the linking of tables from different data sources to aid in database deconstruction.
Qlik
Qlik provides self-service data analytics and a business intelligence platform that supports both cloud-based and on-premises deployments. This tool offers robust support for data exploration and discovery for both technical and non-technical users alike. Qlik also allows users to customize a range of chart types using both built-in SQL modules and drag-and-drop features.
SAS Business Intelligence
SAS offers a collection of applications for self-service analytics, featuring numerous built-in collaboration tools such as mobile report delivery. Although SAS is a comprehensive and flexible platform, it may be more expensive than some competitors. However, larger enterprises often find its versatility justifies the cost.
Tableau
Tableau is a leading data visualization and analytics platform that empowers users to create and share reports across desktop and mobile systems or embed them in applications. A significant portion of the Tableau platform is based on a foundational query language, which effectively translates drag-and-drop dashboards and visualization components into backend queries, minimizing the need for end-user performance enhancements.
Microsoft Excel
Excel is a fundamental and widely-used analytical tool across almost all industries. It plays a vital role in analyzing internal client data and handles the complex task of summarizing datasets through pivot tables to filter data according to client requirements. Excel also includes advanced business analytics features that enhance modeling capabilities with pre-built options.
R Programming
R is a leading analysis tool in the industry, extensively used for statistical tasks and data modeling. It readily processes and presents data in various formats. R has excelled in multiple areas compared to SAS, particularly with data handling, performance, and outcomes. It operates across various platforms, including UNIX, Windows, and macOS, and boasts over 11,556 packages, allowing users to browse packages by category.