Analytics and business go hand-in-hand. Data helps set key performance indicators, help an organization better understand its clients, measure business performance, and can dictate the entire direction of a business.
Businesses have more than enough data sources to pull from, including: historical records, revenue data, and customer behavior information and more to drive strategic decisions.1 However, the information has little value as raw data. Organizations rely on data analytics software, and professionals who know how to use these business intelligence tools, to analyze and extract actionable insights from their data.
With the wide array of business intelligence platforms available, however, it can be challenging to know where to start with business intelligence and when conducting a data analytics software comparison. Read on to explore the top business intelligence tools and how businesses use them to make sense of big data.
Tableau is a business intelligence (BI) tool that enables companies to visualize data.2 Organizations use it to connect business data from different sources, including spreadsheets, databases and the cloud.3
One feature that makes Tableau a powerful data analytics software is that it combines artificial intelligence (AI) and analytics. It uses the Einstein Discovery AI to identify patterns in a company’s historical business data and predict future trends.4 This enables an organization to anticipate risks it might face and make data-driven decisions to mitigate or prevent them from happening.
Tableau’s drag-and-drop interface makes it easy to customize interactive dashboards and create visualizations such as maps, charts, and graphs.5 It’s also among data analytics platforms that provide a suite of solutions:
- Tableau Desktop for creating and publishing visualizations6
- Tableau Server for sharing and collaborating on data across an entire organization7
- Tableau Prep for cleaning data before analysis8
Tableau is one of the most commonly used business intelligence tools because of its intuitiveness, powerful visualization capabilities, and suite of useful tools.9
Microsoft Power BI
Microsoft Power BI is a collection of software tools that work together to turn data into visual insights. It’s one of the most popular data visualization platforms in the market–about 97% of Fortune 500 companies use Power BI.10
The tool’s easy-to-use interface makes it helpful to both technical and non-technical users.11 Microsoft Power BI also allows users to find the link between unrelated datasets through charts or graphs.12 This visualization makes it easy to identify how a variable, such as sales, changes over time or under different economic conditions.
Another notable feature of Microsoft Power BI is its data discovery capabilities. With Power BI an organization’s data can be centralized from multiple data sources. It allows companies to bring together all of their data sources in one platform to establish a single source of truth.11 This breaks down data silos between an organization’s departments since each team has a comprehensive view of the company’s data.13
Furthermore, the tool integrates with other software solutions an organization might use, such as Salesforce, Google Analytics, and Microsoft Dynamics.14 This ensures Microsoft Power BI fits seamlessly into an organization’s existing workflows.
Amazon QuickSight is a cloud-based, serverless business intelligence tool. Since QuickSight works in the cloud, businesses don’t need to set up and maintain an on-premise server infrastructure. This makes Amazon QuickSight more affordable than traditional BI solutions.15
Additionally, the platform eliminates business intelligence silos by enabling users in an organization to create, schedule, and share reports from a central place.16 Another excellent feature of QuickSight is generative capabilities. Instead of manually translating analyzed data into understandable terms, users can ask QuickSight to generate insights automatically. As a result, organizations can quickly extract important information from their data and make informed decisions faster.17
With over 150 chart types, 7000+ custom maps, and a drag-and-drop user interface, Domo is a robust but simple data visualization solution. Similar to Amazon QuickSight, Domo comes with natural language technology. That means business professionals can use text instead of code to ask Domo to generate insights from datasets.18
Furthermore, the analytics software has a descriptive analytics module for generating AI-powered insights.18 With descriptive analytics, Domo can analyze a company’s historical data — traffic reports, financial statements and market trends — to identify patterns and help answer the question, “What happened?”19
The analytics software accepts data from multiple data warehousing tools, including Oracle, MS SQL Server, and IBM DB2.20
Looker is a powerful business intelligence platform made by Google. Like most data analytics software, Looker allows users to explore and visualize data through a user-friendly interface. Data analysts can use it to create customizable dashboards, user-tailored reports, and charts to gain valuable insights into their data.21
What sets Looker apart from the rest is its modeling language, LookML. Data scientists and business analysts can use LookML to specify how different datasets are related to each other.22 This is important for generating deeper insights and creating a meaningful representation of the data being analyzed.
Additionally, Looker has robust access control and security features, which explains why thousands of organizations use it.23 It has multiple access permission levels for limiting who can create, read, or delete data inside the platform. It also allows companies to restrict access to information based on a person’s position in the corporation.21
Zoho Analytics is a self-service BI platform, which means businesses can use it to analyze data and create insights without help from IT specialists. The platform has three million active users, which isn’t surprising considering its outstanding features.24
Zoho Analytics has a data preparation and management tool that businesses can use to prepare datasets in the following ways before analysis:
- Data cleaning: Correcting errors and inconsistencies to improve the quality of datasets
- Data enrichment: Adding supplemental information to existing data to make it more valuable
- Data transformation: Modifying or converting the structure, format, or values of a dataset to make it more suitable for analysis
After preparation, organizations can process the data with AI. Zoho’s conversational assistant (Zia) can analyze data with human-like intelligence, generate insights from data sets, and predict future trends based on patterns it identifies in the input.24
Businesses can also use Zoho Analytics to create dashboards and customize reporting tools with the platform’s drag-and-drop interface. They can visualize data using pivot tables, charts, and widgets.24
After preparing, analyzing, and visualizing data inside Zoho, users can share files, set up access permissions, and comment on reports.24
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- Retrieved on November 16, 2023, from forbes.com/sites/adigaskell/2016/10/28/becoming-a-data-driven-organization/?sh=367ae4a94121
- Retrieved on November 16, 2023, from tableau.com/why-tableau/what-is-tableau
- Retrieved on November 16, 2023, from help.tableau.com/current/pro/desktop/en-us/basicconnectoverview.htm
- Retrieved on November 16, 2023, from tableau.com/products/einstein-discovery
- Retrieved on November 16, 2023, from help.tableau.com/current/pro/desktop/en-us/buildmanual_dragging.htm
- Retrieved on November 16, 2023, from tableau.com/products/desktop
- Retrieved on November 16, 2023, from tableau.com/products/server
- Retrieved on November 16, 2023, from tableau.com/products/prep
- Retrieved on November 16, 2023, from simplilearn.com/tutorials/power-bi-tutorial/power-bi-vs-tableau
- Retrieved on November 16, 2023, from powerbi.microsoft.com/en-us/blog/microsoft-business-application-summit-recap/
- Retrieved on November 16, 2023, from microsoft.com/en-us/power-platform/products/power-bi/
- Retrieved on November 16, 2023, from learn.microsoft.com/en-us/power-bi/fundamentals/power-bi-overview
- Retrieved on November 16, 2023, from blog.hubspot.com/website/single-source-of-truth
- Retrieved on November 16, 2023, from learn.microsoft.com/en-us/power-bi/connect-data/service-connect-to-services
- Retrieved on November 16, 2023, from aws.amazon.com/pm/quicksight/
- Retrieved on November 16, 2023, from aws.amazon.com/quicksight/
- Retrieved on November 16, 2023, from aws.amazon.com/quicksight/generative-bi/
- Retrieved on November 16, 2023, from domo.com/features#bi-analytics
- Retrieved on November 16, 2023, from online.hbs.edu/blog/post/descriptive-analytics
- Retrieved on November 16, 2023, from trustradius.com/products/domo/reviews?qs=pros-and-cons#product-details
- Retrieved on November 16, 2023, from trustradius.com/products/looker/reviews?qs=pros-and-cons#product-details
- Retrieved on November 16, 2023, from cloud.google.com/looker/docs/what-is-lookml
- Retrieved on November 16, 2023, from cloud.google.com/blog/products/data-analytics/looker-product-2021
- Retrieved on November 16, 2023, from zoho.com/analytics/