Business Intelligence leverages software and services for drawing out meaningful insights from the collected data. 

  Since its inception in 2003, Tableau has been the favourite software amongst business leaders to drive business intelligence. It is a visual analytics platform transforming the way businesses use data to solve problems. It allows the user to explore, manage data, discover and share insights that can alter the business outcomes. However, over the past few years, the deployment of Tableau amongst businesses has significantly reduced. Business intelligence guides an organization to make informed decisions by transforming data into meaningful insights through leveraging software and services. Many companies are now coming up with software that has the potential to deliver a positive outcome in business intelligence and can be utilized as an alteration to Tableau. In this article, we will navigate through the top business intelligence software that will drive business intelligence in the future.  

1. Domo

Domo is a powerful business intelligence software with a wide dataset and connector support. Its unique collaboration capabilities make it one of the widely used software to assist the business in finding effective solutions in the competitive business world.  With Domo, the user can deliver high-quality data insights in a few minutes or seconds which was not possible earlier. Having more than 500 data connections to update in real-time and extensibility through SKD, the connected data is analyzed with the help of visual editor without any need for special coding knowledge. Data visualization in Domo can be done through the mobile application, and without any need for a broader screen.  

2. GoodData

GoodDataoffers two products to its users: End-to-end data platform and embedded analytics. With the help of embedded analytics, the company can deliver a wide range of customizations, create product tiers to deliver custom analytics to different customer segments, and frequently release new analytical features and distribute changes across customers. Its centrally managed analytics distribution includes betas, early access launches, and more-to each product audience. Due to the GoodData’s fault-tolerant data pipeline, the software is capable to ingest terabytes of data for thousands of users at regular intervals. With its comprehensive monitoring and alert integration, the software reduces the risk of data mishandling. This is particularly incorporated in smaller corporations, who are planning to improve the data analytics quality, but are unable to commit full data management system,  

3. Dundas BI

Dundas BIis an enterprise-ready Business Intelligence (BI) platform for creating and viewing interactive dashboards, reports, scorecards and more. The businesses can deploy Dundas BI as the central data portal for your organization, or integrate it into an existing website as part of a custom BI solution. The Dundas BI allows self-service business intelligence, full API support, latest web standards including HTML5, Mobile and Touch, Data Visualisations, ETL layer and In-Memory Analytics. Extract-Transform-Load (ETL) capability is built directly into Dundas BI via our data cube layer. By simply adding transforming nodes to a data cube and connecting them to perform data cleansing or combine data from different sources, the output of a data cube can be stored in the company’s internal data warehouse for improved performance. It also contains an in-memory analytical model of the users’ data to enable even faster results for analytical queries.  

4. InsightSquared

InsightSquaredis the complete revenue intelligence platform, which automatically syncs deal activity and engagement so that the business can analyze the sales process. As activity data is the number one indicator of sales outcomes, InsightSquared automates, connects and write-the full team’s activities back to the customer’s CRM. It helps the customers to discover whether the activities of the sales team has completed, the steps they missed, and how prospects responded, so the businesses can drive more consistent, predictable results. Moreover, it records, transcribes and analyzes every customer’s call across the entire sales journey. By capturing transcripts, keywords, trends, and talk time, the software then combines conversation data with full-lifecycle activity capture and robust machine learning, to enrich every element of the customer’s business such as forecasts, reporting, product roadmaps, marketing campaigns, and competitive positioning, amongst others.  

5. SAS Business Intelligence and Analytics

Founded in 1976, SAS analytics is designed for use in a variety of industries including government, manufacturing, higher education, defence and security, banking and much more. Its business analytics reveals patterns and anomalies in data, identity relationships and different variables for predicting future outcomes. SAS analytics platform assists in data mining, data visualizations, text analytics, forecasting, and statistical analysis.  

6. Sisense

Often cited as truly the alternative of Tableau, Sisense Business Intelligence and Data Analytics software, unifies multiple data sources into one centralized location. The user can easily join data from multiple locations with little to no help from IT, leaving plenty of time to concentrate on analyzing the data for insights instead of scripting and coding. With the help of Sisense, businesses can choose from hundreds of built-in connectors to join multiple data sources and formats.  

7. TIBCO Spotfire

Spotfireis an AI-powered, business intelligence software designed for search-driven experience with built-in data wrangling and advanced analytics It is the most comprehensive analytics solution in the market and makes it fast and easy for everyone to visualize discoveries in data. Using search and recommendations powered by a built-in artificial intelligence engine, anyone using this software can explore data to bring insights.   Spotfire delivers numerous capabilities at-scale, including visual analytics, data wrangling, predictive analytics, location analytics, and streaming analytics.