Gartner’s Magic Quadrant for Business Intelligence 2016

Gartner’s latest Magic Quadrant for Business Intelligence has been released and Microsoft Power BI has been named as a “Leader”, ahead of Tableau and Qlik.


Gartner Magic Quadrant for Business Intelligence 2016


Organizations seeking to stay ahead of the competition recognize the importance of investing in analytics and visualization tools to deliver insights from their data. They need a modern, powerful business intelligence (BI) platform that will stand up as an industry leader and a vision that will meet the needs of tomorrow.

Industry analysts have taken note of our efforts and we are excited to share Gartner has positioned Microsoft as a Leader, for the ninth consecutive year, in the Magic Quadrant for Business Intelligence and Analytics Platforms.* For the first time, Microsoft is placed furthest in vision within the Leaders quadrant.

The establishment of an updated modern BI and analytics platform definition for this year’s Magic Quadrant has significantly transformed the Leaders quadrant relative to is composition in previous years. In a market that is rapidly evolving with new innovation being introduced constantly, leaders in the BI market must demonstrate that they are focused not only on current execution but have a robust roadmap that will solidify its position as a future market leader, protecting the investment of today’s buyers.

The strong placement for Microsoft could only have been made possible through the hard work of our many engineers and testers who listened over the years to users of Excel and Power BI to expand the capabilities and drive new benefits. We also must thank the more than 90,000 organizations in 185 countries that are now using Power BI.

Just as businesses strive to find an edge against industry foes, Microsoft is determined to deliver modern BI and analytics solutions for all types of users and to remain a leader and visionary in a competitive BI platform environment. Microsoft and Power BI stand out — and the benefits pay off for users.

The technologies behind Power BI enable users to create and share insights in real time. With Power BI, anyone can develop rich and compelling stories that perfectly visualize data. And Power BI is continually upgraded by our community of engineers, partners and users, so the tools get better every day.

Read more about Microsoft’s standing in Gartner’s 2016 report and learn how businesses can make a competitive difference here. We also recommend reading Gartner’s report, “New Microsoft Power BI Is an Enhanced Offering at a Compelling License Price.





The Forrester Wave™: Agile Business Intelligence Platforms, Q3 2015

Forrester made Microsoft LEADER in terms of being able to provide Agile Business Intelligence (Q3 2015)! Whoooyaaahh!
Meer info, click here.

Forrester Wave Agile Business Intelligence Platforms Q3 2015









And don’t forget, we’re also leader in terms of: Gartner’s Magic Quadrant for Operational Database Management Systems (2015)




Gartner’s Magic Quadrant for Operational Database Management Systems (2015)

Whoooyah…Microsoft is number 1, numero uno 🙂

Gartner Magic Quadrant for Operational Database Management Systems 2015


Read the full article here:

Headquartered in Redmond, Washington, U.S., Microsoftmarkets its SQL Server DBMS for the operational DBMS market, as well as the Microsoft Azure SQL Database (a DBMS platform as a service), and the NoSQL DBMSs Microsoft Azure DocumentDB and Azure Tables.



  • Market vision:

Microsoft’s market-leading vision consists of NoSQL (Azure DocumentDB and Azure Tables), cloud offerings (including hybrid cloud), the use of analytics in transactions (HTAP) and support for mobility. Its vision for in-memory computing across products, hybrid cloud implementations and a “cloud first” strategy is ahead of its competitors.

  • Strong execution:

Microsoft SQL Server is an enterprisewide, mission-critical DBMS capable of competing with products from the other large DBMS vendors. Gartner’s 2014 market share data shows Microsoft as the No. 2 vendor in terms of total DBMS revenue.

  • Performance and support:

Reference customers were very positive, with the performance of SQL Server, documentation, support, ease of installation, integration and operation all rated highly.


  • Market image:

Although SQL Server is an enterprise-class DBMS, Microsoft continues to struggle to dispel a perception of weakness in this area. Inquiries from Gartner clients demonstrate a continuing perception that SQL Server is not used for mission-critical enterprisewide applications — a view that inhibits wider use of SQL Server as a primary, enterprise-class DBMS.

  • Lack of an appliance:

Microsoft still lacks an appliance for transactions (one comparable to its Microsoft Analytics Platform System, formerly Parallel Data Warehouse). By contrast, its major competitors (IBM, Oracle and SAP) all offer one, as does one new entrant to the Magic Quadrant (Fujitsu).

  • Pricing:

Microsoft received below-average ratings for pricing suitability, a problem that stems from the pricing model changes implemented in SQL Server 2012. Microsoft’s cloud offerings appear to be partially mitigating this concern.


Gartner’s Magic Quadrant for Business Intelligence and Analytics Platforms 2015

Today Gartner’s Magic Quadrant for Business Intelligence and Analytics Platforms 2015 spread across the internet.

Gartner’s Magic Quadrant for Business Intelligence and Analytics Platforms 2015

Here’s a comparison between 2013, 2014 and 2015:

Magic Quadrant for Business Intelligence and Analytics Platforms 2015 Comparison

Read the full report here:

The Microsoft BI and analytics product portfolio supports a diverse range of centralized and decentralized BI use cases and analytic needs for its large customer base. Organizations typically deploy SQL Server and SharePoint to support IT-developer-centric data management, reporting and administration requirements, while business-user-oriented, self-service data preparation and analysis needs are delivered by the Power BI components of the portfolio through Excel 2013 and Office 365. Business-user enablement is a clear focus of Microsoft’s product road map and business model evolution — as evidenced by its new “freemium” Power BI product offering (currently in preview), which can be deployed as a stand-alone solution for business users to author and share analytic content without the need for Excel 2013 or an Office 365 subscription.
Microsoft’s leadership position in the Magic Quadrant is primarily driven by a strong product vision and future road map, as well as a clear understanding of the market’s desire for a platform that can support systems-of-record requirements and deliver easy-to-use data discovery capabilities, with support for promotability of business-user content and governance. Power BI has gained some traction, but has yet to gain widespread market acceptance due to the complexity of on-premises deployments and the relatively limited functionality currently delivered through the Office 365 cloud; barriers which Microsoft is trying to address with the new Power BI offering currently in preview and due to be released later in 2015. As Power BI matures and cloud adoption grows, Microsoft is positioned to leverage its large customer base (and capitalize on the already pervasive use of Excel and the existing SQL Server Analysis Services footprint in the market) to expand the breadth and depth of its deployments in organizations and increase its overall BI and analytics market share, if it can increase its focus on BI sales and marketing and overcome customers’ structural barriers to adoption.

Overall cost of ownership and license cost remain the top reasons customers choose Microsoft (according to the survey). Microsoft has integrated good capabilities into Excel such as Power Query, Power Pivot, Power View and Power Map, which are included with existing enterprise license agreements. Additional cloud-based consumption and collaboration capabilities are currently available in Power BI through a subscription-based pricing model in Office 365. Microsoft recently announced a freemium license model for its new stand-alone Power BI offering, which includes Power BI Designer for content authoring, set to be officially released during 2015 and featuring a free tier for up to 1GB of data storage per user and a Power BI Pro option for up to 10GB available for $10 per user per month (significantly reduced from the Power BI version currently offered through an Office 365 subscription).
Many organizations already use Microsoft Excel extensively for data manipulation and presentation of information through spreadsheets, which gives Microsoft a strong foundation on which to build with Power BI and close the gap between it and the data discovery leaders. A key differentiator for Microsoft is its ability to deliver a range of business user capabilities, encompassing self-service data preparation with Power Query and Power Pivot, interactive visualization through Power View and Power Map and the ability to share with SharePoint and Office 365, which few vendors can claim without third-party support and partnership. Platform scalability is a strength of the Microsoft platform, which ranked highest for data volume accessed — with an average data size of 62TB, compared with an overall average of 14.2TB.
Microsoft reference organizations also report deployment sizes larger than those of any other vendor in this Magic Quadrant, with an average number of end users of 6,000 compared with an overall average deployment size of 1,554. With the release of the new stand-alone version of Power BI, business users will have access to built-in connectivity to on-premises SQL Server Analysis Services cubes, which will allow organizations to leverage existing data assets without having to move to replicate in the cloud and further unlock the value of existing multidimensional data structures.
Microsoft products scored well in its traditional areas of strength: BI administration and development, and integration and collaboration. They also scored highly on business-user data mashup — an area of investment for Microsoft with Power Pivot and Power Query.
Reorganization and new leadership at Microsoft appears to be positive for Microsoft BI. Since taking over, new CEO Satya Nadella has made support for Apple and Android devices, as well as cloud deployment, a high priority.

Microsoft’s product portfolio is complex and includes many components, which can cause confusion for customers evaluating purchase options. The fact that many of the newer capabilities that are important to buyers in this market require current versions of Office, SQL Server and SharePoint adds to the complexity and represents a barrier to adoption for many organizations that are on older versions and are not yet willing to buy Office 365 and deploy BI and analytics in the cloud. For example, the workflow between components such as Power Query, Power View and Power Pivot is not yet completely seamless. Moreover, the role of SharePoint dashboards and Reporting Services has not been clearly articulated; Reporting Services is not supported in Azure. While it is a work in progress, Microsoft is attempting to address many of these limitations in the forthcoming stand-alone version of Power BI, which does not require Office 2013 or an Office 365 subscription and can access Analysis Services structures and content without physically moving underlying enterprise data to the cloud.
Microsoft had the highest percentage of customer references citing absent or weak functionality (for example, no drill-through capabilities in Power View) as a platform problem. This is consistent with last year’s results; and while Microsoft is addressing weakness in mobility, analytic dashboards and free-form interactive exploration with Power BI, market awareness and adoption has been slow to materialize — as shown by minimal client inquiries since its launch in early 2014.
Microsoft’s sales model continues to be a pain point for customers, who rated Microsoft fourth lowest for overall sales experience. Customers have historically found it difficult to engage directly with Microsoft during the sales cycle, which was a major complaint from IT but is an even greater concern for Microsoft as it attempts to appeal to business buyers that have high expectations of simplified license models and purchase options.
Microsoft has a large network of implementation partners and developers that are skilled in most aspects of traditional centralized BI deployments. However, customers may have difficulty finding external resources with experience in the newer Power BI stack, which requires a different set of skills and expertise than Microsoft’s sweet spot of systems-of-record, developer-focused BI deployments.

Previous reports by Gartner:
Gartner’s Magic Quadrant for Business Intelligence and Analytics Platforms 2014, click here for the full report by Gartner.

Gartner: Magic Quadrant for BI Platforms 2013

Top 10 Strategic Technology Trends for 2015 by Gartner

Again, also 2015 will be a great year for BI! 🙂

Gartner, Inc. today highlighted the top 10 technology trends that will be strategic for most organizations in 2015.

Gartner defines a strategic technology trend as one with the potential for significant impact on the organization in the next three years. Factors that denote significant impact include a high potential for disruption to the business, end users or IT, the need for a major investment, or the risk of being late to adopt. These technologies impact the organization’s long-term plans, programs and initiatives.

“We have identified the top 10 technology trends that organizations cannot afford to ignore in their strategic planning processes,” said David Cearley, vice president & Gartner Fellow. “This does not necessarily mean adoption and investment in all of the trends at the same rate, but companies should look to make deliberate decisions about them during the next two years.”


Advanced, Pervasive and Invisible Analytics
Analytics will take center stage as the volume of data generated by embedded systems increases and vast pools of structured and unstructured data inside and outside the enterprise are analyzed. “Every app now needs to be an analytic app,” said Mr. Cearley. “Organizations need to manage how best to filter the huge amounts of data coming from the IoT, social media and wearable devices, and then deliver exactly the right information to the right person, at the right time. Analytics will become deeply, but invisibly embedded everywhere.” Big data remains an important enabler for this trend but the focus needs to shift to thinking about big questions and big answers first and big data second — the value is in the answers, not the data.

Read the full article from Gartner here.

Magic Quadrant for Data Warehouse Database Management Systems

Thank Gartner for the info.

Entering 2014, the hype around replacing the data warehouse gives way to the more sensible strategy of augmenting it. New competitors have arisen, leveraging big data and cloud, while traditional vendors have invested — which will force improved execution from new technology companies.

For this Magic Quadrant, we define a DBMS as a complete software system that supports and manages a database or databases in some form of storage medium (which can include hard-disk drives, flash memory, and solid-state drives or even RAM). Data warehouse DBMSs are systems that can perform relational data processing and can extended to support new structures and data types, such as XML, text, documents, and access to externally managed file systems. They must support data availability to independent front-end application software, include mechanisms to isolate workload requirements (see Note 2) and control various parameters of end-user access within managed instances of the data.

A data warehouse is a solution architecture that may consist of many different technologies in combination (see Note 3). At the core, however, any vendor offering or combination of offerings must exhibit the capability of providing access to the files or tables under management by open access tools. A data warehouse is simply a warehouse of data, not a specific class or type of technology.

In 2014, this Magic Quadrant introduces non-relational data management systems for the first time. No specific rating advantage is given regarding the type of data store used (for example, DBMS, Hadoop Distributed File System [HDFS]; relational, key-value, document; row, column and so on). All vendors are expected to provide multiple solutions (although one approach is adequate for inclusion), each demonstrating maturity and customer adoption. Also, cloud solutions (such as platform as a service) are considered viable alternatives to on-premises warehouses.

A data warehouse DBMS is now expected to coordinate data virtualization strategies, and distributed file and/or processing approaches, to address changes in data management and access requirements.

Magic Quadrant for Data Warehouse Database Management Systems 2014


Microsoft ( markets SQL Server 2012 (Service Pack 1 has been available since November 2012), a reference architecture and the parallel data warehouse appliance. Microsoft does not report customer or license counts. Gartner estimates Microsoft’s relational DBMS revenue grew 13.6% during 2013 — faster than the overall market.

– Microsoft offers appliances, reference architectures including a variety of hardware, prebuilt offerings built to customer selections then delivered ready to run, software licensing and managed services data warehouses.
– Customers report a low count of software issues, above-average customer experience and obvious interoperability with Excel (and Office).They also like the easy-to-understand licensing and pricing — adding to execution.
– Customers are predominantly on the current release, and almost 60% of customers report it is their data warehouse standard. Microsoft has taken steps in pursuing the LDW with HDInsight (HDP for Windows), PolyBase and Microsoft Cloud (Windows Azure Infrastructure Services can be used to deploy a data warehouse).

– Microsoft is catching up with the other leaders, but a fast-follower market demand still drives the Microsoft road map. However, Microsoft has demonstrated its willingness to be aggressive in certain areas (such as unstructured data via SharePoint search and Azure).
– Organizations report large volumes of data but, in general, Microsoft data warehouses have a small number of users — better examples of scaling warehouses are needed. Customers want easier access to usable metadata for heterogeneous environments.
– Reference customers still report a significant cost advantage, but inquiries indicate that even small price increases do matter and Microsoft needs to maintain its price differentiation from other vendors.

More info.

Gartner’s Magic Quadrant for Advanced Analytics Platforms 2014

Gartner’s Magic Quadrant for Advanced Analytics Platforms 2014

Predictive analytics and other categories of advanced analytics are becoming a major factor in the analytics market. We evaluate the leading providers of advanced analytics platforms that are used to build solutions from scratch.

It’s such a pivotal moment for data scientists and the growing open-source R community that Gartner has embarked on its first ever Magic Quadrant for Advanced Analytics Platforms. Gartner estimates advanced analytics to be a $2 billion market that spans a broad array of industries globally, and ‘Gartner predicts business intelligence and analytics will remain top focus for CIOs Through 2017.’ We believe that this new Magic Quadrant puts a spotlight on big data as the great analytics disruptor which we feel highlights the need for solutions like Revolution Analytics’ that are built upon a flexible, open platform, and designed for today’s Big Data Big Analytics challenges.” — Dave Rich

Magic Quadrant for Advanced Analytics Platforms 2014

Gartner’s Magic Quadrant for Business Intelligence and Analytics Platforms 2014

Gartner’s Magic Quadrant for Business Intelligence and Analytics Platforms 2014

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.

Magic Quadrant for Business Intelligence and Analytics Platforms 2014

More info:
Gartner’s Magic Quadrant for Business Intelligence and Analytics Platforms 2014

Gartner’s Magic Quadrant for BI Platforms 2013

Gartner’s 2013 Hype Cycle for Emerging Technologies

Gartner published it’s annual ‘Hype Cycle for Emerging Technologies‘ and (like it always does) it inspires!
Read the full article here.

Here it is, this year’s Hype Cycle!

Gartner’s 2013 Hype Cycle for Emerging Technologies

And like you would have guessed, the hot topics this year are:

Source: Gartner August 2013
The 2013 Emerging Technologies Hype Cycle highlights technologies that support all six of these areas including:

1. Augmenting humans with technology


Technologies make it possible to augment human performance in physical, emotional and cognitive areas. The main benefit to enterprises in augmenting humans with technology is to create a more capable workforce. For example, consider if all employees had access to wearable technology that could answer any product or service question or pull up any enterprise data at will. The ability to improve productivity, sell better or serve customer better will increase significantly. Enterprises interested in these technologies should look to bioacoustic sensing, quantified self, 3D bioprinting, brain-computer interface, human augmentation, speech-to-speech translation, neurobusiness, wearable user interfaces, augmented reality and gesture control.

2. Machines replacing humans
There are clear opportunities for machines to replace humans: dangerous work, simpler yet expensive-to-perform tasks and repetitive tasks. The main benefit to having machines replace humans is improved productivity, less danger to humans and sometimes better quality work or responses. For example, a highly capable virtual customer service agent could field the many straightforward questions from customers and replace much of the customer service agents’ “volume” work — with the most up-to-date information. Enterprises should look to some of these representative technologies for sources of innovation on how machines can take over human tasks: volumetric and holographic displays, autonomous vehicles, mobile robots and virtual assistants.

3. Humans and machines working alongside each other

Bald is beautiful

Humans versus machines is not a binary decision, there are times when machines working alongside humans is a better choice. A new generation of robots is being built to work alongside humans. IBM’s Watson does background research for doctors, just like a research assistant, to ensure they account for all the latest clinical, research and other information when making diagnoses or suggesting treatments. The main benefits of having machines working alongside humans are the ability to access the best of both worlds (that is, productivity and speed from machines, emotional intelligence and the ability to handle the unknown from humans). Technologies that represent and support this trend include autonomous vehicles, mobile robots, natural language question and answering, and virtual assistants.
The three trends that will change the workforce and the everyday lives of humans in the future are enabled by a set of technologies that help both machine and humans better understand each other. The following three areas are a necessary foundation for the synergistic relationships to evolve between humans and machines:

4. Machines better understanding humans and the environment
Machines and systems can only benefit from a better understanding of human context, humans and human emotion. This understanding leads to simple context-aware interactions, such as displaying an operational report for the location closest to the user; to better understanding customers, such as gauging consumer sentiment for a new product line by analyzing Facebook postings; to complex dialoguing with customers, such as virtual assistants using natural language question and answering to interact on customer inquiries. The technologies on this year’s Hype Cycle that represent these capabilities include bioacoustic sensing, smart dust, quantified self, brain computer interface, affective computing, biochips, 3D scanners, natural-language question and answering (NLQA), content analytics, mobile health monitoring, gesture control, activity streams, biometric authentication methods, location intelligence and speech recognition.

5. Humans better understanding machines


As machines get smarter and start automating more human tasks, humans will need to trust the machines and feel safe. The technologies that make up the Internet of things will provide increased visibility into how machines are operating and the environmental situation they are operating in. For example, IBM’s Watson provides “confidence” scores for the answers it provides to humans while Baxter shows a confused facial expression on its screen when it does not know what to do. MIT has also been working on Kismet, a robot that senses social cues from visual and auditory sensors, and responds with facial expressions that demonstrate understanding. These types of technology are very important in allowing humans and machines to work together. The 2013 Hype Cycle features Internet of Things, machine-to-machine communication services, mesh networks: sensor and activity streams.

6. Machines and humans becoming smarter
The surge in big data, analytics and cognitive computing approaches will provide decision support and automation to humans, and awareness and intelligence to machines. These technologies can be used to make both humans and things smarter. NLQA technology can improve a virtual customer service representative. NLQA can also be used by doctors to research huge amounts of medical journals and clinical tests to help diagnose an ailment or choose a suitable treatment plan. These supporting technologies are foundational for both humans and machines as we move forward to a digital future and enterprises should consider quantum computing, prescriptive analytics, neurobusiness, NLQA, big data, complex event processing, in-memory database management system (DBMS), cloud computing, in-memory analytics and predictive analytics.

Previous Hype Cycles:

Gartner’s 2012 Hype Cycle for Emerging Technologies

Gartner’s 2011 Hype Cycle for Emerging Technologies