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Comparative Analysis of BI Reporting Tools

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Business intelligence (BI) reporting tools help an organization gather, consolidate, and derive value from its raw data. These tools allow users to analyze their data in-depth, improving decision-making at every level in the organization. Various BI reporting tools are about 80-85% similar in terms of functionalities and features. Different BI tools cater to different user needs like Self Service Reporting, Advanced Analytics, Enterprise-level reporting, etc.
There are certain expectations from a BI reporting tool when it comes to evaluating them based on the below-mentioned parameters:

1. Self Service: Self-service business intelligence (SSBI) is an approach to data analytics that enables business users to access and work with corporate data even though they do not have a background in statistical analysis, BI, or data mining.
An ideal self-service BI reporting tool should qualify on the below-mentioned parameters:


Visualization & Intuitiveness: Ability to present KPI Driven Visual aids for quickly getting a business pulse at that time.
Data Blending: Ability to join/blend data from multiple sources like excel and data marts.
Report Templates: Ability to create report templates and reuse them
Web-Based Modifications: Ability for end consumers/users to change the format of the report, slice and dice, and save it.
Export Functionality: Ability to export data to PDF, Excel, and other commonly used platforms.
Report Sharing: Ability to deliver a report to a mailbox or any specific location.
Self-Scheduling and Refresh: Ability for user to self-subscribe to schedules or refresh reports on-demand/event-based.

2. Advanced Analytics: Advanced analytics goes beyond mathematical calculations such as sums and averages. It generates new information, identifies patterns and dependencies, and calculates forecasts.
An ideal advanced analytics BI reporting tool should qualify on the below-mentioned parameters:

Data Capturing: Ability to enable processing and analysis of large amounts of data.
Data Mining: Data and text mining may be used to find specific trends or pieces of data.
Predictive Analysis: Ability to use techniques associated with data mining, machine learning, statistical analysis, and others to generate highly accurate predictions about future business trends
Statistics: Ability to figure out what future trends or results might come about based on the statistics being reviewed

3. Enterprise level reporting: Enterprise reporting is the creation and distribution of reports concerning business performance to key decision-makers in an organization. This may include reports on metrics on key performance indicators or information curated for day-to-day activities. Various factors such as operational reporting, database connectivity support, and user authentication are essential from an enterprise standpoint.
An ideal enterprise-level BI reporting tool should qualify on the below-mentioned parameters:

Data authorization: Data authorization with inheritance from business application
Vendor support for tool: There should be easy-to-access vendor support for the tool.
Pixel-perfect reporting: Ability to make reports which can be formatted in their components down to the individual pixel level

Let us consider 3 leading BI reporting tools and evaluate them based on different parameters.

MicroStrategy: MicroStrategy is an enterprise analytics platform that delivers Dashboards, Visualizations, Mobile apps and supports custom solutions.

Salient features:
Reusability: Metadata created in MicroStrategy can be reused in the same project many times
Supports Self Service BI: Supports Self Service BI along with other powerful tools to create reports/dashboards
Supports a full range of BI applications: Supports a full range of BI applications from departmental BI (small workgroups) to Enterprise BI
Massive Data access: Can access massive amounts of data from different data sources like EDW and Transactional


Tableau: Tableau helps in simplifying raw data in a very easily understandable format. Data analysis is very fast with Tableau, and the visualizations created are in the form of dashboards and worksheets.
Salient features:
Supports Self Service BI: Designed from the ground up to support self-service
Visual Analytics Capabilities: Provides robust visual analytics capabilities to enable data discovery with rapidly promoted roll up and drill-down capabilities
Data Blending: Easy to use report data blending options facilitate merging multiple data sources
Server Component Features: The server components provide scalability, access authorization, scheduling, and governance
Distribution: Distribution is via a variety of client interfaces like Web Browser and Mobile


Power BI: Power BI enables users to gather business insights from both on-premise and cloud-stored data in a dynamic, interactive visualization at the low cost of ownership.
Salient features:
Content Packs: Power BI uses Content Packs, which has dashboard reports, data models, and embedded queries.
Custom Visualization: Power BI has a library of custom visualization. If the business needs are different, then so should the visuals.
Access to a variety of Data sources: Power BI Desktop includes a huge array of on-premise and cloud data sources.
Print Dashboard: Power BI provides a unique feature for printing dashboards, which can be handy in board meetings and discussions.
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About the Author

Kshitij Talhar is a Technical and Operations Lead for Business Intelligence at Perficient. Kshitij has over 7.5 years of experience in Business Analytics, Consulting, Administration, Data Modelling, Solution Design, and Development, mainly focusing on implementing data analytics using MicroStrategy and Tableau.

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