The Best Business Analytics Software

We’re here today to talk about the Magic quadrant for business intelligence and analytics platforms, which is published annually by Gartner.

We hope to answer questions like –


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  • Is SAS the best software in Analytics ?
  • What is the standing of Microsoft when it comes to Analytics (Excel , Access , SQL)
  • How good is Tableau in the eyes of the Analytics world?


(What is Gartner?  Gartner is the world’s leading IT research and advisory company which delivers technology related insights from CIOs and senior IT leaders in corporations to the general public .All of us use Gartner and its reports to come to conclusions about the various software suites we would like to buy.)

Over the last decade, the world of business intelligence and analytics has undergone a change. As organisations have adopted business intelligence and started looking at the data for measurement and reporting purposes, the next level was to try and do prediction forecasting and optimisation on the same data. Because of this growing importance of advanced analytics, the organisation started looking at solutions which could deliver end to end services. Over the last few years we see software suits which have both BI and predictive analytics capabilities.

Thus Analytics software as of today are expected to be able to provide services across 17 categories

  1. Reporting
  2. Dashboards. What is the difference between reporting and  dashboards ? It is a style of reporting that uses a lot of graphics to show performance measures
  3. Ad-hoc reports and queries
  4. Microsoft Office integration
  5. Mobile BI-  which enables organisations to develop and deliver content on mobile devices
  6. Interactive visualisation -which enables the exploration of data via the manipulation of chart images. This includes an add in of visualisation options that go beyond the normal pie chart, bargraph etc. and could include heat and tree maps scatter plots other special-purpose visuals etc.
  7. Search-based data discovery – this applies a search index to structured and unstructured data sources
  8. Geospatial and locational intelligence- which is specialised analytics and visualisations that provide a geography, spatial and a time context
  9. Embedded advanced analytics -which will enable users to levitate statistical functions library embedded in the BI server
  10. Online analytical processing or OLAP- this allows users to analyse data with fast query and calculation performance enabling slicing and dicing of data
  11. BI infrastructure and Administration -which enables all tools in the platform to use the same security , meta data , query engine etc. That platform should support multi tenancy.
  12. Meta data management
  13. Business user data modelling- which would be free drag-and-drop user driven data combinations
  14. Development tools
  15. Embeddable analytics -which would be tools including a software developer’s Kit with APIs for creating and modifying analytical content, visualisations etc. and embedding them into a business process
  16. Collaboration -which would enable users to share and discuss information analysis chat etc.
  17. Support for big data sources -which is the ability to support and query hybrid, columnar and array-based data sources, such as MapReduce and other NoSQL databases

(source:- )

[highlight]What does Gartner say about SAS ? I am sure this is the question that’s in your mind . Since I started my Analytics journey with SAS , it is the most important question in my mind .[/highlight]

1.      SAS

SAS’s analytics portfolio spans platforms for BI, performance management, data warehousing, in-memory databases, data integration, data quality, decision management, and content and social analytics, with a core strength being advanced analytics. SAS also offers industry- and domain-specific analytic applications built on its product portfolio.


  • SAS’s analytics portfolio spans platforms for BI, performance management, data warehousing, in-memory databases, data integration, data quality, and content and social analytics. However, unlike most other BI platform vendors, SAS’s core strength is in its advanced analytical techniques, such as data mining, predictive modeling, simulation and optimization, for which it is acknowledged as a Leader in “Magic Quadrant for Advanced Analytics Platforms.”
  • Historically, SAS tools have been used primarily by power users, data scientists and IT-centric BI developers. That this remains the case is shown by SAS customers placing it above any other vendor in the Magic Quadrant survey in terms of support for complex types of analysis, but giving it one of the lowest scores for ease of use. During the past five years, SAS has been investing heavily in revamping its user experience to change this situation and encourage more mainstream user adoption. This aggressive and unmatched strategy is part of the reason for SAS’s favorable Completeness of Vision position.
  • SAS also differentiates itself from most other BI platform vendors by productizing and selling industry- and domain-specific advanced analytic applications that are focused on specific business problems and built using many of its technology platform products. This enables it to sell “value,” rather than components.
  • Data access and integration and the ability to support large volumes of data are the main reasons customers choose SAS, according to the survey. In fact, while SAS deployments support a below-average number of users, its data volumes are among the highest in the survey.


  • SAS customers consider its software among the most difficult to use and most difficult to implement, with ease of use for business users being identified as a limitation on broader deployment by a higher percentage of customers than for any other vendor.
  • Although SAS has exploited its core competency in predictive analytics to encapsulate and automate advanced analysis for business-user-oriented guided data discovery in Visual Analytics, it will face competition from data discovery and BI and analytics platform vendors with leading-edge data discovery capabilities, such as Tableau and Tibco.
  • Despite SAS’s success as a Leader in the predictive analytics space, the company still faces a challenge to make it onto BI platform shortlists, unless customers already use its other advanced analytic capabilities and require integration and leverage of skills.
  • SAS’s reference customers rated functionality used in traditional BI areas (reporting, dashboards, OLAP, interactive visualization and so on) lower than for most of the other BI Leaders



Microsoft Excel 2010 with its analysis toolpak has been quoted by me as being one of the most easy-to-use analytics tools. Let’s see what Gartner says about Microsoft.


2.      Microsoft

Microsoft offers a competitive and expanding set of BI and analytics capabilities, packaging and pricing that appeal to Microsoft developers, independent distributors and now to business users. It does so through a combination of enhanced BI and data discovery capabilities in Office (Excel) 2013, data management capabilities in SQL Server, and collaboration, content, and user and usage management capabilities in SharePoint.


  • Of the megavendors, Microsoft has made the most progress toward delivering a combination of business user capabilities with an enterprise-capable platform. Microsoft delivered business-user-oriented data discovery and other BI capabilities in Excel 2013.
  • Microsoft has made early investments in its cloud-based BI offering, Power BI. Microsoft’s strategy is to use the cloud to increase adoption of its new and most competitive BI capabilities in Excel (starting with Excel 2013), and to accelerate enhancements to Excel to every six months.
  • n the customer survey conducted for this Magic Quadrant, more Microsoft customers cited TCO and license cost as their main reasons for selecting Microsoft as a BI vendor than did those of most of the other vendors.
  • Microsoft composite product score was above average across the 17 capabilities, when weighted for use. Microsoft customers appreciate its strong BI infrastructure and development tools. They also rated its reporting, ad hoc query, Microsoft Office integration, business user data mashup, embedded BI, collaboration, search BI and OLAP capabilities higher than the survey average. Importantly, unlike those of its megavendor competitors, Microsoft’s customers rated customer experience (support and product quality) above the survey average.


  • Although Microsoft’s functional ratings have improved and it can offer a wide range of functions, it also has one of the highest percentages of users who say that absent or weak functionality is among the main reasons limiting broader deployment of its software. Mobile BI, interactive visualization and metadata management remain product weaknesses reported by customers.
  • Multiproduct complexity remains a challenge, now primarily for on-premises and hybrid deployments. Because Microsoft’s BI platform capabilities span three different tools (Office, SQL Server and SharePoint) that also perform non-BI functions, the task of integrating components and building applications is left mainly to the customer.
  • Although Microsoft’s partner-driven sales model drives global growth for the company, Gartner’s inquiries suggest that this approach often makes it difficult for customers to find their Microsoft sales representative. This causes frustration .


[highlight][/highlight]I increasingly see Tableau becoming an integral part of the reporting structure in most KPOs. Let’s see what the Gartner’s report has to say about this software.

3.  Tableau

Tableau’s highly intuitive, visual-based data discovery, dashboarding, and data mashup capabilities have transformed business users’ expectations about what they can discover in data and share without extensive skills or training with a BI platform.


  • Tableau offers an intuitive, visual-based interactive data exploration experience that customers rate highly .Its core differentiator — making a range of types of analysis (from simple to complex) accessible and easy for the ordinary business user, whom Tableau effectively transforms into a “data superhero.
  • Tableau has a focused vision with an evolutionary road map for enabling users to meet enterprise requirements for reusability, scalability and embeddability. Tableau’s strong survey results for customer satisfaction, coupled with its market momentum, are behind its dominant Ability to Execute position.
  • Tableau provides purpose-built, business-oriented data mashup capabilities with data connectors that use Tableau’s VizQL technology. Direct query access has been a strength of the platform since the product’s inception. Tableau offers a broad range of support for direct-query SQL and MDX data sources, as well as a number of Hadoop distributions, native support for Google BigQuery, and support for search-based data discovery platforms, such as Attivio.


  • Although Tableau’s average user count continues to grow and was above the market average in this year’s customer survey, its products are often used to complement an existing BI platform standard; only 42% of its customers considered it as their BI standard.Ttraditional BI platform vendors with substantial installed-base market shares but lacking in growth momentum, including IBM, Microsoft, MicroStrategy, SAP and SAS, are aggressively investing in their own data discovery capabilities to reverse the trend.
  • Tableau’s customers report a below-average sales experience, which includes the entire sales life cycle from presales activities to contracting, pricing and the ongoing sales relationship.
  • Tableau continues to expand its international presence, but the majority of its customers are likely to be large (often international) companies located in North America. Tableau has opened sales offices in Europe and Asia (for example, Singapore) and introduced support in Asia; it also plans further global sales expansion with live, time-zone-appropriate support in local languages.


Subhashini Tripathi
From 2002 onwards, Subhashini has a decade of experience across roles in Analytics in Retail Finance and Banking. These roles have been across Risk Management , Collections strategy , Fraud Control and Marketing in GE Money, Standard Chartered Bank, Tata Motors Finance and Citi GDM . Her area of interest is the integration of results / outputs of Analytics with Business Decisions – Tactics and Strategy. She is currently active in the Analytics Training and Consulting arena.

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