Talking in terms of velocity, variety and volume, big data is constantly growing and is disrupting today’s business landscape.
Big Data or the large chunk of raw data- both structured and unstructured, is increasingly being collected, stored and analyzed by organizations to create new opportunities, optimize business processes and take better decisions.
IDC estimates that the amount of information stored in the world’s IT systems is doubling about every two years. By 2020, the total amount will reach to 6.6 stacks from the earth to the moon.
With having far more intelligence at their disposal, companies are facing some big big data challenges, which include storing and analyzing large and diverse data sets and handling them. Traditional data processing applications seem to be inadequate for the purpose – too expensive to scale or adapt to rapidly evolving conditions.
So, managing data is a growing challenge and organizations are turning to a number of different modern analytics and business intelligence (BI) tools that are affordable and can help them store, process, and query all their data.
Analytics and Business Intelligence have transformed the market and have given rise to new buying trends from IT-centric system of record (SOR) reporting to business-centric agile analytics with self-service.
The IT market is flooded with multiple BI and analytics platform providers but significant differences remain in functionalities. So, one should assess which BI and analytics products are best for their organization depending upon the use cases needed by each business function and the product.
Top 5 use cases for a Business Intelligence and Analytics platform:
- It should support agile centralized BI provisioning.
- It should support extranet deployment for external customers or in the public sector.
- It should support decentralized analytics – workflow from data to self-service analytics.
- It should support governed data discovery.
- It should support work flow form data to embedded BI.
While choosing from modern BI solutions, a business should also look for certain critical capabilities that a BI platform should include.
Critical Capabilities for Business Intelligence and Analytics Platforms
Modern BI and analytic platforms’ architecture should provide its users with certain capabilities. Like, it should enable its users to easily access advanced analytics capabilities, provide highly interactive and analytic dashboards, help to find, visualize and narrate important findings, automatically.
It should support platform deployment, both on premises and in the cloud, and ensure high availability and disaster recovery.
Platform should support metadata management and self-contained Extraction, Transformation and Loading (ETL) and Data Storage, Self-Service Data Preparation, Scalability and Data Model Complexity.
Analytics and BI solutions should support mobile authoring and exploration i.e. enable organizations to develop and deliver content to mobile devices.
Platform should be easy to use, visually appealing and should allow users to publish, share and collaborate on analytic content.
Top 10 Business Intelligence tools 2018 comparison: Microsoft vs Tableau vs Qlik vs IBM vs Oracle
Gartner’s Magic Quadrant for Analytics and Business Intelligence Platforms 2018 is out. Not all Business Intelligence platforms are alike. All of them perform differently and support different workflow capabilities, hence have been rated and positioned accordingly by Gartner.
We will be comparing top 10 analytics and business intelligence platforms in our blog series. This blog post is the first part of a two-post series on different analytics and business intelligence platforms.
Microsoft offers Power BI, a suite of business analytics tools to deliver insights; produce and publish reports; and for data preparation, personalized & interactive dashboards; data discovery and augmented analytics. This Microsoft business intelligence software is available both as a SaaS option and on premises, and is one of the lowest-priced solutions in the market today.
Gartner has positioned Microsoft in the top quartile. It is among leaders for the 11th consecutive year, due to prominent levels of customer interest and adoption.
Power BI Desktop can be used as a stand-alone, free personal analysis tool and is also required when power users are authoring complex data mashups involving on-premises data sources. Main criteria for buying this business intelligence and analytic platform solution is primarily its cloud deployment model, visual appeal, ease of use, low per-user and virtual server subscription price.
User enablement and the availability of skilled resources are other elements of the overall customer experience for which Microsoft is evaluated as above average.
Tableau offers interactive data visualization products- Tableau Desktop, Tableau Server and cloud offering – Tableau Online to help users to access, prepare, analyze and present findings through their data, without technical skills or coding.
This advance data visualization tool, which is focused on business intelligence, provides analytic dashboarding capabilities and extensive set of data connectors, for any data source. It allows customers to visualize and understand data, connect to any (almost) database, drag and drop to create visualizations, and share with a single click.
Tableau is also placed in Leaders Quadrant for its efforts to build product awareness worldwide, augmented data preparation and, discovery and agile data cataloging.
As per Gartner, the business Intelligence (BI) and data visualization tool, Tableau, scores very high for its ease of use and the user experience that it delivers. It is rated excellent by customers for the ethics and culture.
Qlik Sense is the Modern BI and analytics platform of Qlik which offers agile analytics and BI along with governed data discovery and allows developers to create customized applications.
With scalable in-memory engine, customers can create, robust, interactive, visual applications and some also use this engine as a substitute of traditional data warehousing. They can use engine as a data mart and get support for complex calculations, multiple data sources and complex data models.
Qlik is positioned in the Leaders’ quadrant for augmented analytics, improvements in its marketing strategy, and ease of use. However, its market execution is rated poor as compared to other leaders due to relatively low momentum.
Cognos Analytics and IBM Watson Analytics are the two complementary BI solutions that IBM offers.
Cognos Analytics is available both on-premises or as a cloud solution on the IBM cloud whereas Watson Analytics is available as a cloud solution, only. They both incorporate augmented analytics capabilities which make them easier to use and more appealing platforms.
Cognos Analytics features include scheduling and alerting, and Cognos Framework Manager models which users can use for new dashboards and explorations. Watson Analytics features include automated pattern detection, embedded advanced analytics and support for NLQ generation.
Gartner has positioned IBM in the Visionaries quadrant this year.
Oracle offers a wide variety of BI and analytics capabilities. It’s Oracle Data Visualization (ODV) offers integrated data preparation, interactive exploration, dashboards, mobile and augmented analytics through a single tool which supports both desktop and web-based authoring.
Oracle Analytics Cloud (OAC) is used for myriad range of analytics use cases — from decentralized to governed and centralized deployments.
Oracle business intelligence platform can be deployed both on-premises and in the Oracle cloud, but Oracle’s reference customer scores place it in the bottom quartile -Niche Players, for operations.
There’s no such best business intelligence solution as most have similar capabilities, and the selection mainly that depends upon your business needs.
Below ratings from Gartner Peer Insights review can form the basis of comparison of best BI tools. These opinions are based on the enterprise users’ own experiences and these ratings are verified by Gartner.
Business intelligence platforms are assessed on the basis of how well they support critical capabilities as set by Gartner.
|Collaboration & Social BI||4||3.9||3.7||3.5||3.6|
|Self-Contained Extraction, Transformation & Loading (ETL) & Data Storage||4||3.6||4.1||3.7||3.8|
|Ease of use to deploy and administer||4.2||4.3||4.1||3.9||3.8|
|Interactive Visual Exploration||4.3||4.6||4.4||3.9||3.7|
|Governance and Metadata Management||3.7||3.6||3.7||3.9||3.8|
|Embedding Analytic Content||4||4.1||4||4||3.7|
|Security and Use Administration||4||4||4.1||4.2||4.2|
|Self-Service Data Preparation||4||3.8||3.9||3.9||3.8|
We will come up with the second article in the series soon. Meanwhile, let us know your feedback in the comments section.