Don’t you wish your Excel was just like me: Modern BI platform reviews

Power BI, Qlik and Tableau under the scope

Modern analytics and BI platforms are now mainstream. For companies big and small, MS excel no longer cuts the mustard when it comes to transforming data into engaging, insight-rich visualisations.

So what are they? Quite simply, analytics and BI platforms are easy-to-use software that supports the full analytic workflow — from data prepping and ingestion to visual exploration and insight generation. What sets them apart from BI platforms of old is that they don’t require hordes of IT staff to predefine data models or store data in traditional data warehouses. Self-service and agility is the name of the game, and providers are springing up everywhere to get a piece of the pie.

As the market grows and options become plentiful, it can be difficult to know which software to choose. To lend a hand, we’ve been through the latest Gartner review of the main players, picking out three that we believe are worth your consideration.

Power BI offers data preparation, interactive data discovery, and advanced analytical options, all in one product. It’s available as a SaaS option running in the Azure cloud or as an on-premises option in Power BI Report Server.

In the analytics space, Microsoft is making a name for itself as a true Leader. It has a comprehensive and visionary product roadmap and is focused on making Power BI accessible for all. It continues to demonstrate strong uptake globally and reports very high levels of customer satisfaction.

The good

  • It’s cheap — Microsoft is putting pressure on the market with its low cost per user, virtual server subscription and embedded capacity-based pricing. Because many companies have existing Microsoft software agreements, it’s also a small step for procurement teams to roll out the software. License cost was the second most important reason for reference customers to choose Microsoft Power BI. Microsoft also came top third of vendors for sales experience — an improvement from the year before.
  • It’s easy to use — Power BI makes complex analysis look easy, with users giving it top-third ratings across all aspects of ease of use. Microsoft’s “first five-minute experience” (which aims to have users register for a trial and be “wowed” within five minutes) and a robust user community contribute to this result.
  • It’s got ambitious plans — Microsoft is investing in a broad set of visionary capabilities and integrating them with Power BI. They’re also focusing heavily on augmented analytics like machine learning and natural language processing. The aim is to make these complex technologies adoptable by people with minimal data science skills. Important roadmap items include full support for existing Reporting Services reports, a common and open data model, and open data preparation with data flows.

The bad

  • Multiple products: Although the core of Power BI is a self-contained product, Microsoft’s roadmap spans multiple products. For example, more robust conversational analytics is supported through the Cortana personal digital assistant. Data scale-up options require multiple products.
  • Differences in on-premises and cloud service with Azure cloud only: Power BI Report Server enables users to share reports (not dashboards) and lacks some of the ML capabilities found in Power BI SaaS. Users also report inconsistencies in the support of different data sources. Microsoft does not give customers flexibility to choose a cloud infrastructure as a service (IaaS) offering, instead running only in Azure.
  • With Power BI, Microsoft has mainly focused on agile, self-service analytics. On-premises SQL Server Reporting Services meets the needs for scheduled, distributed reports. This has resulted in a two-product deployment with different capabilities and different deployment approaches. Reporting Services content authoring and report distribution in Power BI is on the short-term roadmap.

Source: Gartner Magic Quadrant for Analytics and Business Intelligence Platforms. See the full review here:

Qlik delivers data discovery and agile analytics via its lead product, Qlik Sense. The platform can be used to build customised applications via an extensive set of APIs, so it supports a huge range of data analytics use cases. Qlik’s original product, QlikView, accounts for a large portion of the company’s revenue — more than 67%. According to customers, Qlik is used primarily for decentralized analytics (70%) and agile centralized BI provisioning (66%) use cases.

In July 2018, Qlik acquired Podium Data to broaden its data management capabilities. Then in January 2019, Qlik acquired Crunch Data so it could provide conversational analytics. In 2018, it launched a new pricing model to encourage QlikView customers to move to Qlik Sense, or to add Qlik Sense to their deployments; it offers dual licenses for a nominal fee.

Qlik’s position in the Leaders quadrant is thanks to its strong product roadmap, geographic reach and market understanding. But its market responsiveness scores are lower than those of other Leaders.

The good

  • Product features and extensibility: Qlik has added augmented features via its Cognitive Engine. Improved self-service capabilities and Insight Advisor help users find useful insights faster with automatic chart generation, as well as suggested insights that the engine thinks may be important. Qlik Core, added in 2018, is a development platform where developers can build applications for cloud or edge deployments. Qlik’s scalable in-memory engine lets customers build robust, interactive, visual applications. It also supports multiple data sources, complex data models and complex calculations.
  • Customer experience: Qlik’s active user community is a key contributor to customers’ high scores for user enablement. These are supported by high scores from Gartner Peer Insights reviewers relating to the quality of the peer user community. Qlik’s business-value-based messaging, Data Literacy Project campaigns, and multiple conference series help to influence the market and stimulate demand.
  • Product vision: Qlik continues to extend and enhance its platform as the market evolves. It handles big data with its On-Demand App Generation and will expand these capabilities with its new Associative Big Data Index. Qlik continues to execute on its augmented analytics roadmap, as well as improve its data preparation and embedded analytics capabilities.

The bad

  • Lots of products: QlikView and Qlik Sense need multiple products to accommodate specific pieces of an analytics workflow. Podium Data, now called Qlik Data Catalyst, will become a stand-alone product to deliver data cataloguing and more advanced data prep.
  • Migration experience: Qlik announced a new pricing model in July 2018, with an option for existing QlikView customers to start using Qlik Sense. However, Qlik’s reference customers score the vendor below average for operations, with the main contributor being low scores for migration experience. When asked to name limitations with regard to wider deployment, Qlik’s customers frequently identified functional differences between QlikView and Qlik Sense. Gartner Peer Insights reviewers also rate Qlik’s service and support as below average.
  • Lower momentum: Qlik reduced its headcount significantly in 2018. Compared with 2017, there has been a slight decline in interest in Qlik from Gartner clients, judging from Gartner’s client inquiry data for 2018 and social media analytics. This was particularly evident for first-time customers evaluating Qlik against other leading vendors in this market.

Source: Gartner Magic Quadrant for Analytics and Business Intelligence Platforms. See the full review here:

Tableau offers an intuitive, interactive experience where you can prepare, analyse and present findings in your data without technical skills or coding. It comes in two forms, primarily as an on-premises software desktop application or as a cloud-based SaaS offering (Tableau Online).

In 2018, Tableau introduced a new, lower-priced Viewer role and now leads with named-user, subscription-based pricing. Tableau Prep was released to improve data preparation and profiling within Tableau Desktop — and more robust server-based scheduling capabilities are in beta testing. Tableau also acquired Empirical Systems in 2018 to broaden its augmented analytics capabilities.

Tableau’s customers report that they use it primarily for decentralized analytics (70%) and agile, centralized BI provisioning (51%).

Tableau is a Leader, thanks to the popularity of its product, high customer satisfaction scores and strong roadmap.

The good

  • Easy visual exploration and data manipulation: Tableau can ingest data from a broad range of data sources, blend them, and visualize results using best practices in visual perception. Data can be manipulated while visualizing — such as when creating groups, bins and new hierarchies — all with a high degree of ease of use.
  • Customers as fans: Customers have a fanlike attitude toward Tableau; a record 17,000 users attended its 2018 annual user conference. Customers placed Tableau in the top third of Magic Quadrant vendors for customer experience, and gave it high scores for achievement of business benefits. Tableau sets the industry standard for Meetup groups, roadshows, online tutorials and availability of skills in the market.
  • Momentum: Tableau grew its total revenue to just over $800 million through 3Q18 — double-digit growth compared with 2017. This was despite moving to subscription-based licensing, which often impairs a vendor’s growth. Tableau remains at the top of many customers’ shortlists, and continues to expand within its installed base. The Tableau Foundation and Tableau Public have been a force in the Data for Good movement, having recently pledged $100 million in funding over the next seven years.

The Bad

  • Product gaps: Support for querying multiple fact tables and complex schemas in a single data source is absent from Tableau’s product. It also doesn’t support scheduled, bursted reports in a variety of output formats, or the promotion of content through development, testing and production processes. Support for bursted reports with output to PDF is on the short-term roadmap.
  • Support decline: The responses of surveyed customers, together with other Gartner research, indicate that the quality of Tableau’s product support declined in 2018. Customers’ responses put Tableau in the bottom third of vendors in this Magic Quadrant, due partly to more difficult upgrades. Hyper was a major engine replacement to boost performance — one that has not gone as smoothly as previous releases. Further, 12% of Tableau’s reference customers say poor performance remains a problem, and 13% say the product cannot handle the required data volumes (both percentages are above the average).
  • Sales experience, contracting and cost: Tableau did well to introduce a new, lower-priced viewer license to compete better against Microsoft in particular, but this license is only available with a subscription license. Consequently, perpetual customers have to move to a new named-user and subscription model to be able to buy this new license. These conversions can be a point of friction, which may explain why Tableau’s customers place it in the bottom third of vendors in this Magic Quadrant for sales experience. Gartner Peer Insights reviewers place it in the bottom third for price and contract flexibility. Over one-third (35%) of Tableau’s customers identified cost as a limitation with regard to wider deployment.

Source: Gartner Magic Quadrant for Analytics and Business Intelligence Platforms. See the full review here:

What we say

Just as a picture paints a thousand words, a good visualisation paints a thousand insights. It’s a key part in your data journey, where you bring your important analysis to life.

Whichever solution you choose, always refer back to your business case and ask: which best supports my business requirements? To get it right, your platform needs to be suitable for the end user, fit your budget, and provide the right level of ongoing support. At Data ³, we’re fans of PowerBI and Tableau, but we’re technology and tool agnostic — we use whatever works best for the project in hand. At all stages, from building the right use cases and extracting the data, to analysing and building models, we provide feedback and ongoing support. If you’re in need of help at any of these stages, visit and get in touch.