The word ‘best’ can be fairly meaningless, and so in this Business Intelligence Tools article I have indicated the products that excel in various areas. You will see a graphic displayed at the side of products which offer capability above the norm.
This article is a work-in-progress and will be compiled into a report some time in the coming month.
Alteryx is an interesting product, filling a void that most other analytic platforms do not address. It allows skilled business users and analysts to analyze their data using a combination of data visualization and predictive analytics tools. It also supports spatial analytics where location is important. Alteryx places a great deal of emphasis on the ease-of-use of its platform and the creation of workflows via a drag-and-drop graphical interface. Resulting analysis can be shared, both the analytic models and the results of analysis. Virtually all commonly used data sources are supported, and via a process of data blending users can shape data into the form they need for analysis. Various analytic techniques can then be applied to the data, and the results output in visual formats and/or formats which can be consumed by other tools (e.g. Tableau and QlikView).
Alteryx is not primarily a data visualization platform, and so is not in the same genre as most business intelligence platforms, where predictive analytics and other more sophisticated forms of analysis are not supported. In a nutshell Alteryx is an advanced analytics platform that has been made approachable through its user interface, and where the results from analysis can be easily shared.
Complex analytics which involve widely diverse data sources are the forte of Alteryx. The platform is easy to use and extremely practical in its application to business problems. It avoids the unnecessary complexity of many other alternatives, while providing sophistication that is not available in most data visualization and business intelligence platforms.
BIME is a contemporary business analytics platform. By this we mean it connects with a wide range of data sources – internal and external, it offers a very easy to use interface, supports extensive collaboration and does all the things that might be expected of a BI solution. All the usual charts are supported, in addition to highly functional maps, relational analysis, funnel charts – all in a very customizable environment.
The mandatory drag and drop environment is used to create charts and dashboards, with built in drill-down, drill through and filtering. Groups, sets and queries can be built with support for advanced calculation, if required.
Data connectivity is a particular feature of BIMS, and particularly external data sources and big data. This includes Google BigQuery, Redshift, SAP HANA, Vectorwise and Vertica. Other connectors include Google Analytics, Facebook Insights data and Twitter analytics, in addition to connectors for internal databases and applications (ERP, CRM etc.). The queries and calculations are optimized for whichever database is being accessed.
Various performance features ensure good performance and data can be loaded up to the cloud if desired. Google BigQuery accounts can be used as a target of the data load. Refreshing data stored in BIME can be scheduled, and runs in the background on a nominated server.
Distribution of documents and collaboration feature strongly in BIME. Dashboards can be embedded into web pages, portals and blogs – or any other service. And every BIME account provides a portal for each dashboard viewer, that lists all the dashboards they have access to, and a timeline of their conversations. From a security perspective, it is not absolutely necessary to upload data to BIME and original data sources can be directly accessed.
Best Cloud BI
Birst is a cloud (public or private) based BI platform that addresses the needs of both production oriented BI and end-user data visualization and querying. The company calls this a 2-Tier approach, and it is possible because of the excellent data management architecture of the platform.
Many contemporary data visualization platforms are, in effect, point solutions. They confuse the data picture rather than clarify it, by creating their own versions of the truth within a database of their own. They also do not cater for production BI needs which, although currently somewhat unfashionable, are nonetheless here to stay. Production reporting (weekly sales reports for example), executive dashboards and other ‘fixed’ information needs will always be with us, despite the current fascination with all things visual.
So Birst competes very well with the ease of use of products such as Tableau and Qlik Sense, while also providing a true enterprise BI facility, with support for regular, production oriented reporting.
The impressive feature list of Birst includes native and offline mobile support, embedded predictive tools, intelligent data functions, automated data refinement, drag and drop data visualizations, and quite unique levels of data management. This integrated environment means that everyone gets the same version of the truth, that predictive models can be embedded into dashboards and charts, and that there should never be data ambiguity.
Best Ease-of-Use
Chartio is a cloud based data visualization platform targeted almost exclusively at the business user. Everything about this product has been engineered to make the task of visualizing data easy. The company is focused pretty much exclusively on revenues from licenses, and so the product has to be easy to use. Competing products often require that customers spend considerable amounts (typically more than half total cost) on training and consulting, and Chartio is on a mission to make this a zero cost.
The target market is small to medium size businesses, although some larger companies use the platform too. Don’t expect any sophisticated statistical analysis, or anything beyond charts, tables and graphs – this is not the platform’s domain.
Getting to data is fairly straight forward, and users can elect to store data in a cloud data warehouse if they wish – Amazon RedShift for example. Joins over diverse data sources are supported, and the results of queries are stored as Chartio datastores, for reuse when needed.
The ease-of-use provided by Chartio is the result of clever interfaces and manipulation behind the scenes. The whole thing is very well thought out, and although not a low cost alternative, it will give business users direct access to their data and the visualizations that provide insights into that data.
ClearStory provides a cloud based platform that takes business users from data to visualization with minimal need for technical skills. In common with several other suppliers (Tamr, Paxata, Platfora and others) it uses machine learning techniques and Apache Spark in-memory processing, to take data from its raw state, to a state where business users can create the data visualizations they need. As data sources become more diverse so businesses are using the Hadoop big data platform as a ‘data lake’, and ClearStory increasingly supports this and many other diverse data sources.
Users are presented with a collaborative environment where data discovery, exploration and visualization efforts can be shared via StoryBoards. These provide one or more visualizations in the context of a story line, and various users can annotate and comment as the StoryBoard evolves.
Terms such as data wrangling, data blending, data curation and governance are increasingly used to describe the effort that is needed to handle complex data, and while we all want easy to use data visualization tools, it is the data preparation, and all that goes with it, that determines the success or otherwise of data visualization. To this end ClearStory is very well positioned for the growing need to handle complex data environments in a data visualization context.
Best Big Data Support
Datameer makes big data, and specifically the Hadoop platform, accessible for business users and analysts. It never was going to be the case that most businesses would employ an army of technicians to wrestle with mapReduce and other aspects of Hadoop, just to make it work. Big data technologies are inexorably being shrink wrapped and given a more approachable interface, and Datameer is at the forefront of this trend. It is no exaggeration to say that Datameer will be a one-stop-shop for many organization wishing to handle big data, and unlike some platforms, it does not display any weaknesses in any of the four primary functions it address – data integration, data preparation, quantitative analytics, and data visualization, although Tableau can be used to further enhance this last area of functionality.
In summary Datameer provides the means to bring large data sets, that display great diversity (text, relational, streaming data etc) into the Hadoop environment. Once there Datameer supplies the data wrangling tools necessary to profile and transform data into useable formats. Analysts and data scientists can then use the large set of algorithms provided by Datameer to create predictive models and perform other forms of quantitative analysis. Finally, business users can visualize data using a wide variety of charts and dashboards, and more advanced visualizations such as clustering and decision trees can be created via an easy-to-use interface.
Datameer Professional is a SaaS big data analytics platform designed for department-specific deployments. It provides a Hadoop as a Service platform for business users to do their own analysis.
Under the hood Datameer has recently been enhanced to optimize workloads, and provides the means to ensure adequate governance and compliance with regulatory authorities. As ‘big data’ becomes more prevalent, as it surely will with the emerging Internet of Things (IoT), so Datameer will find itself in a prime position to address the needs of many organizations. It is largely unchallenged for its ability to make big data useful to those who most need to use it – business analysts and users.
Domo is a cloud BI solution that is targeted at larger businesses, and majors on ease-of-use, social sharing of information and transparent access to diverse data sources. The actual analytic capability is on a par with most other offerings of this genre, but since the platform is geared toward business users the emphasis is primarily simple analytics made available in the simplest way possible. For more complex analytics users will need other tools, but Domo will address the general need for reporting and data visualization for many business users who simply want to see their data in an easily digested format, and with least possible effort. Support for mobile devices and a native iPad app enhance the availability of information considerably.
GoodData is a cloud based BI platform, well known for its ease of use. In fact GoodData was one of the earlier cloud BI platforms to emerge, and has been fine tuned for business users to get direct access to their data. The platform does pretty well everything – data visualization, data access and integration, a columnar data warehouse, collaboration, and tools for governance and management. GoodData does claim advanced analytics, but in reality these are little more than basic statistical functions – linear regression, correlation, frequency and several others. This is not really advanced analytics, but is a useful augmentation to the usual set of charts, maps and tabular data representations.
The platform is particularly targeted at sales and marketing activities, and GoodData supplies a number of solutions in this domain. More generally GoodData uses the collective experience of its users to provide ‘best practice’ recommendations on visualizations, KPIs and other metrics. This is delivered through its Insights Engine, which sits on top of the data warehousing service.
This is not a particularly sophisticated platform, but it does serve the needs of business users who simply want to see their data in easily digested formats. And along with most other suppliers in this genre, GoodData utilizes a columnar database for the multidimensional processing many visualizations require. The user interfaces are primarily graphical in nature using drag and drop to create visualizations, and users can add approved data sources as needed.
So the positioning of GoodData is fairly straight forward. It is a cloud based data visualization platform for business users to explore and view their data using a variety of common visual formats. It is not an advanced analytics platform (clustering, logistic regression etc), and it cannot be easily extended to incorporate bespoke visual formats. However business users do like the ease-of-use and the best-practice recommendations that the platform provides.
Best Planning and Forecasting
IBM Cognos is a large, sprawling suite of products that will address every conceivable business intelligence requirement. Whether it does it with flair and efficiency is another matter. The platform will only be of interest to large corporations who have well established needs for production reporting, planning, budgeting, forecasting and what-if analysis. It does all these things very well, but the new age of self-service data visualization and exploration seems to be of secondary importance to Cognos. IBM’s leading data visualization technology tends to be associated with its big data products. This is not to say that Cognos does not address data visualization, but it’s definitely not as light on its feet as products such as Tableau and Qlik Sense.
Of course a large part of the Cognos suite comes in the form of TM1 – the planning, forecasting and budgeting applications and tools. Again, a facility of this magnitude will only be of interest to the largest businesses, with a substantial OLAP engine at the heart of the product.
Mobile support is good, with native applications for iPad, iPhone and Android devices. These provide a great deal of functionality, and are not just report and dashboard viewing apps. They work offline too if needed, with processing of local downloaded data sets.
Cognos comes in three flavors. Cognos Insight is a desktop platform for individual use, and it can play its part as a workstation in a larger Cognos deployment. I cannot imagine that anyone would use Cognos Insight as a stand-alone tool outside Cognos Enterprise (although they probably do!). Cognos Express is positioned as a platform for departments and medium size businesses, and can be extended with various add-ons. Cognos Enterprise is the full deployment and comes with a sophisticated architecture.
I have to admit that it is hard to get excited about IBM Cognos, with images of Victorian buildings full of accountants thumping away on calculators. Yes, it’s a little bit unfair to position it this way, but Cognos needs to reinvent itself if it is to appeal to the new mood for democratized, self-service business intelligence.
If an organization is heavily invested in IBM technologies then Cognos is certainly one alternative. But there is a shift taking place in the way businesses use business intelligence technologies, and Cognos is lagging to some extent.
Inetsoft provides a highly functional Bi platform capable of addressing sophisticated reporting needs through to end user data visualization. Power users are able to build the visualizations they need, although Inetsoft is more focused building production data visualizations and as such compares with QlikView, rather than data exploration platforms such as Tableau and Sisense. However neither of these address production reporting needs.
Around 40% of Inetsoft’s business comes from OEM customers and the embedding of BI functionality into other applications. Direct users of Inestsoft include some big names, and the scalable architecture means demanding BI requirements can be met.
There are four editions of Inetsoft’s technology:
- Style Intelligence includes everything, including that data mashup capability, dashboards, charts and reporting.
- Style Scope does not include reporting capability, but does include the charts and dashboards, and so it is more of a data visualization platform.
- Style Report is the reporting module without any visualizations.
- The Agile Edition is actually free, but does not come with any security features and can only connect to spreadsheets and some of the more popular databases. It supports two users.
Best Value
InfoCaptor is available through the cloud, or can be installed locally – in both cases it provides a browser interface. Technically this is a very competent offering, with a bewildering number of chart types, and the facility to easily create and distribute dashboards.
The drag and drop interface means business users can create their own, ad-hoc BI solutions and data visualizations, and a large number of database and other data source connectors mean that composite reports and charts can be easily created. The widgets (various chart components) are said to be ‘data aware’, meaning that they can accept everything from manually entered data to database connections and connections to web services.
All in all, InfoCaptor is an extremely capable product. Unlike many of the products in this space that focus more on ‘bling’ than real capability, InfoCaptor will satisfy many needs and at a very reasonable cost. Take a look – the web site contains plenty of useful information, and is not a triumph of form over content, as so many product web sites are in this space.
Information Builders (IB) provides its WebFOCUS BI and analytics platform to address the information needs most businesses have. This company has been around a long time and really understands how businesses use information and the tools they need to get at it. The reporting tools are some of the most advanced available and address complex requirements – from compliance to HR reporting. Dashboards, mobile support, graphs, charts self-service BI and embedded BI applications are all available, both hosted in-house or through the cloud.
WebFOCUS RStat is an integrated BI and data mining environment, using an engine based on R. This should be of interest to many organizations wishing to integrate analytics with BI, and in this respect IB is well ahead of the pack. In practical terms it means predictive models can be integrated into standard BI delivery mechanisms such as dashboards and reports, providing another dimension for users after maximum insight.
The WebFOCUS Performance Management Framework (PMF) is an out-of-the-box solution for performance management. It comes with pre-built dashboards, hundreds of pre-defined metrics, strategy mapping, mobile alert support, scorecards and many other features.
IB also provides a data integration architecture which supports a bewildering array of data sources, and data integrity tools to maximize as far as possible the accuracy and consistency of data.
Best Embedded BI
Logi Analytics provides two platforms: the operations oriented Logi Info BI platform, and the newer Logi Vision data visualization and exploration platform. The company aims to cater for the needs of three types of user – analysts and power business users who need a free format environment to visualize and explore data, business users who need BI ‘applications’ and do not have the time or inclination to build their own, and developers who need a productive environment to build BI applications. In summary, the two platforms provided by Logi cater for enterprise wide BI needs, with reporting, dashboards, charts, data visualizations, portals and other information formats all within easy reach of this very capable platform.
Logi Analytics has been around for over a decade and is particularly well established as a production reporting environment. It also supports very sophisticated embedding, so that BI applications can be made to operate within operational systems. However the company has recently invested heavily in data visualization and exploration products – specifically Logi Vision. And new in version 12 is the DataHub, a centralized component for data connection, manipulation, enrichment and integration. It also provides a columnar database for multidimensional analysis in Logi Vision. It comes with connectors for a wide variety of data sources including databases (MySQL, SQL Server, Oracle etc.), applications (NETSUITE, SAP, QuickBooks etc.), cloud applications (salesforce, eloqua, Marketo etc.) and files (Excel, CSV).
The capability offered by Logi is very broad, and there are no reasons why a business might not use it as an enterprise BI solution. And while Logi is a bit late to the data visualization party, the company has clearly emulated the best of what is out there and improved on it. Logi Vision compares well with many other leading data visualization platforms, including Tableau and Qlik Sense. But it equally competes with IBM Cognos and Microstrategy, and offers a less monolithic environment in which to satisfy production BI needs, as well as data visualization and exploration.
Logi Analytics has not achieved the popular status of some other suppliers, but after considerable investment it now has products to compete with the best in the BI world – the rest depends on marketing – as always. provides two platforms: the operations oriented Logi Info BI platform, and the newer Logi Vision data visualization and exploration platform. The company aims to cater for the needs of three types of user – analysts and power business users who need a free format environment to visualize and explore data, business users who need BI ‘applications’ and do not have the time or inclination to build their own, and developers who need a productive environment to build BI applications. In summary, the two platforms provided by Logi cater for enterprise wide BI needs, with reporting, dashboards, charts, data visualizations, portals and other information formats all within easy reach of this very capable platform.
Logi Analytics has been around for over a decade and is particularly well established as a production reporting environment. It also supports very sophisticated embedding, so that BI applications can be made to operate within operational systems. However the company has recently invested heavily in data visualization and exploration products – specifically Logi Vision. And new in version 12 is the DataHub, a centralized component for data connection, manipulation, enrichment and integration. It also provides a columnar database for multidimensional analysis in Logi Vision. It comes with connectors for a wide variety of data sources including databases (MySQL, SQL Server, Oracle etc.), applications (NETSUITE, SAP, QuickBooks etc.), cloud applications (salesforce, eloqua, Marketo etc.) and files (Excel, CSV).
The capability offered by Logi is very broad, and there are no reasons why a business might not use it as an enterprise BI solution. And while Logi is a bit late to the data visualization party, the company has clearly emulated the best of what is out there and improved on it. Logi Vision compares well with many other leading data visualization platforms, including Tableau and Qlik Sense. But it equally competes with IBM Cognos and Microstrategy, and offers a less monolithic environment in which to satisfy production BI needs, as well as data visualization and exploration.
Logi Analytics has not achieved the popular status of some other suppliers, but after considerable investment it now has products to compete with the best in the BI world – the rest depends on marketing – as always.
Best Platform for Complex Applications
Looker is definitely different from most of the contemporary BI platforms now crowding the market. The emphasis is much more on the transformation of raw data into a form that makes sense to the business. Many BI platforms come with a metadata layer, but Looker goes well beyond most other products. It also connects directly to data sources, with no intermediary data warehouse, although in some respects this is just semantics, since it needs the services of a query based database (HP Vertica for example). So the real differentiator is that it does not come with its own data warehouse, but uses the services of external databases.
Of course Looker does all the usual things – charts, dashboards, reports, collaboration and so on. However it calls upon a central repository of data and metric definitions like few other products do. This is both a strength and a weakness. It does ensure that the whole enterprise sees one version of the truth. However those users who might want to ‘do their own thing’ will feel inhibited to some extent.
At the heart of Looker is its modeling language, LookML. It is no exaggeration to say that LookML can often perform a task in just a few lines of code that might require hundreds of lines of SQL. This language facilities a ‘just-in-time’ approach to data processing, where transformations and calculations are calculated when needed (officially called a late-binding model). This obviates the need to perform many ETL type operations and formatting of data.
Looker is best suited to organizations with the necessary discipline to create an enterprise wide BI facility with centrally defined functionality. The modeling language facilitates complex data transformation and the calculation of complex metrics. It may be overkill for some businesses, but it does open new possibilities for greater data analysis sophistication.
Despite the claims that data can be accessed in its raw state, some caution should be exercised. BI platforms hardly ever go directly to data held in transaction databases, and so it is always necessary to perform some type of extract and load – and Looker is no different. However its support for many SQL based data warehouse (Spark, Vertica, Teradata, Pivotal, PostgreSQL, MySQL etc), combined with its late binding model, means that data doesn’t have to be shaped for one set of requirements, with the danger that other needs are poorly catered for.
Microstrategy is a very broad, and very deep business intelligence platform. It will primarily be of interest to large corporations with complex requirements, and a very large body of users who need reports and dashboards. While it does address the current vogue for all things visual, it is not as proficient, or easy to use, as products such as Qlik and Tableau. It does however go well beyond the remit of platforms such as these, with integrated advanced analytics for scoring, and industrial strength production reporting capabilities. By Microstrategy’s own admission, users are still uncovering capability after a decade of use.
The main complaint heard is that of the high price. Microstrategy comes in various ‘modules’, and if an organization wants the whole set, it can turn out to be pretty expensive. But there is a value for money argument to be made here, since the high price is rewarded with almost unlimited sophistication.
The platform is an integrated whole – not a trivial accomplishment for so large a product. Developers delight in the object oriented architecture, which often has the pleasant effect of increasing productivity as the sophistication of a deployment increases. The user interface is primarily browser based, with various well defined layers in the architecture below this.
Unless your business is as large or as complex as General Motors or Exxon it may be overkill, and some of the more visual oriented products might be more suitable. Although Microstrategy does offer sophisticated visual analytics in its portfolio of capabilities.
The most recent release is Microstrategy 10 Secure Enterprise – with an obvious focus on security. This is an essential feature when enterprise wide, highly distributed intelligence is being employed. It ties in with Microstrategy Usher – a device based security protocol deployed on mobile devices – and the Apple Watch.
In summary, Microstrategy is a good choice for large organizations with sophisticated needs, pursuing a one product does all approach. The other approach is best-of-breed, with the advantage of a better fit, but at the cost of managing disparate platforms.
Most Disruptive Platform
Microsoft Power BI is disruptive technology. It upsets the equilibrium in the market for expensive data visualization tools, and it makes business intelligence available to a whole new genre of user. And no one should think that Power BI is unsophisticated. Microsoft is on a mission, and in September 2015 alone, over 40 significant enhancements were made to the product.
Until recently Power BI was essentially a set of add-ons for Excel with cloud sharing. Power Pivot supports the creation and manipulation of pivot tables, Power View allows users to explore and visualise data, Power Query is a data manipulation tool for joining and preparing data for analysis. Excel aficionados love the power and flexibility of these tools, but they do present a barrier for those without Excel skills. And so early this year Microsoft introduced a desktop data visualisation tool initially called Power BI Designer, later to be renamed Power BI Desktop. In addition to this they also released the cloud based Power BI Preview, a platform to share dashboards and charts.This is now called the Power BI service. All the functionality of Power Pivot, Power View, and Power Query are embedded into Power BI Desktop, and Microsoft has stated that it is this that will see most development above the Excel add-ons. The user interface incorporates Q&A, the natural language query facility, and optionally Cortana, the speech interface, has also been incorporated. Power BI comes as part of Office 365 Enterprise, and it should be remembered that Microsoft products represent the most widely used BI platform on the planet.
Of course full utilization of Power BI implies some level of buy-in to Microsoft’s wider analytics technologies. A connector exists for SQL Server Analysis Services, and various Azure data sources are also well supported. Real-time dashboards can be created using Azure Stream Analytics, and in a business setting, sharing can be controlled using Office 365 groups. Having said this, the Microsoft Power BI Personal Gateway acts as a bridge to many on-site data sources outside the Microsoft ecosystem.
That Microsoft is serious about business analytics is well demonstrated by its recent acquisition of Revolution Analytics, an enterprise platform for R, the open source statistics and analytics language. It also acquired Datazen, the mobile BI platform, which has been reincarnated as a set of native Power BI apps for all mobile devices. And then earlier this year it introduced Azure Machine Learning – a platform for the development and deployment of predictive analytics.
Microsoft, along with Amazon (who recently introduced its own cloud based business analytics platform) are set to commoditize business intelligence, and the word commoditize should not be read as lowest common denominator. Microsoft Power BI is starting to challenge many premium BI and data visualization platforms, and will ultimately eclipse many of them.
Best Intelligent BI
Panorama would look like many contemporary business intelligence platforms – charts, dashboards and so on. However in many ways Panorama is ahead of the game and offers a platform with in-built intelligence to help users discover and explore, and ultimately establish causality. Since data exploration and discovery is often carried out with the aim of establishing some form of cause and effect relationship, clearly this is a useful feature. In fact all a user has to do is home in on a particular data element and click the ‘Cause and Effect’ button, for related information to be displayed.
The BI platform delivered by Panorama is called Necto, and it rests on four pillars:
Visualization through infographics, and not just the usual bar charts and scatter plots. These truly are infographics aimed at conveying a message.
The Suggestive Engine supports smart data discovery, and understands the nature of the data and the relationships between the various sources.
Collaboration is a major feature in Necto, with support for annotations on charts, through to knowing who else might have an understanding of the data being worked on.
Governance is well catered for, with fine control over who sees what.
The whole environment is supported with guided suggestions, and users create, communicate and work on WorkBoards – effectively smart dashboards. Necto learns as the platform gets used, allowing it to make more accurate suggestions.
Most data sources are supported including databases, online apps, files and more contemporary columnar databases such as HP Vertica.
This is not just another dashboard and charting platform, and Panorama allows users to handle high levels of data complexity through the support provided by its suggestive engine. The net result is that users get the answers they need in much less time, improving both productivity and accuracy.
Prognoz provides a broadly based BI capability with several types of analysis – specifically OLAP, time-series-analysis, and modeling and forecasting. It also provides end-user tools, and specifically the ability to create charts and dashboards. However it does not compete with the likes of Tableau and Qlik Sense for data exploration and visualization. And although it provides ample support for various data sources, it is also lacking end-user data mashup capabilities, where a user might want to create their own combination of data and manipulate it in a unique manner. A variety of vertical and horizontal solutions are provided to cater for corporate, public sector and financial service business needs.
All-in-all this is an unusual offering with a tightly integrated architecture, and will address the BI needs of many businesses. The development and data management tools are particularly sophisticated, and Prognoz provides good integration with the Microsoft technology stack (Office and .NET).
Best Data Discovery
Qlik Sense is a drag-and-drop data visualization and discovery platform capable of addressing most business intelligence needs apart from heavy duty production reporting. It delivers an easy-to-use interface suited to all levels of skill, and has a substantial amount of in-built intelligence to help users along. Charts, tables and dashboards are its main currency, of almost any level of complexity – or simplicity. Users can share their visualizations via various mechanisms and the platform was built ground up for mobile access – no matter the device (visualizations are rendered in HTML5).
Perhaps the most significant Qlik Sense differentiator is its associative data engine. This understands the links between various data sources and can suggest previously unsuspected relationships. Many suppliers use the term ‘data discovery’, but this facility adds new meaning to the term.
It comes in two versions – Qlik Sense Desktop, which is free to download and is not throttled in any way. It runs on a Windows desktop and is capable of accessing many data sources. Qlik Sense Enterprise runs on a server(s) and provides users with a browser based interface. Both editions have similar functionality, but the server platform can scale to serve global distributed enterprises through its excellent scalability and distributed architecture. Qlik has always offered excellent governance of its environment, and IT has the tools to ensure data is secure, unambiguous and that the right people get to the right data.
Very importantly Qlik Sense is extensible. Not a very sexy attribute perhaps, but one that distinguishes the adults from the children in the world of enterprise business intelligence. In fact Qlik Sense is one large extension, built on itself! A large number of APIs are available for embedding visualizations into production applications, creating custom data connectors and building new visualization types. Developers will have absolutely no problem extending Qlik Sense, if that is what is needed. Finally Qlik Sense is fast – its in-memory columnar associative engine guarantees that.
Qlik Sense is the perfect fit for organizations who need easy-to-use data visualization and discovery tools, but may also want the head room to accommodate more advanced levels of sophistication. It is an enterprise solution, with its governance and developer support capabilities. Businesses looking for an enterprise production reporting platform (invoices etc) should look elsewhere, as should users who needs a few simple charts, since they would find Qlik Sense overkill.
Qlik Sense does not come with any advanced statistical or predictive analytics capability, but that is not its domain.
SAP Lumira is a relatively new component in SAP’s somewhat fragmented BI suite of products. SAP Business Objects is the IT centric production BI platform, which has some limited self-service capability, but is certainly not competitive with the swathe of new products now available. In an attempt to address this shortfall SAP has introduced Lumira. It comes in several versions. The Standard Edition is for individual use, The Edge Edition for SMEs and teams, Server Edition for the enterprise , and a Cloud Edition for – well, a cloud deployment. There is nothing particularly interesting here, and Lumira is most likely to be adopted by businesses already heavily invested in SAP technology.
In a broader context the SAP BI ecosystem does address all that most large organizations might want to do with their data. It is in effect a one-stop-shop with ETL, master data management, data warehouse, reporting (Crystal Solutions), production BI (BusinessObjects) and data quality functions. SAP’s acquisition of KXEN also adds advanced analytics, although KXEN was never a broad data mining and statistics toolkit, but is more focused on specific functions (typically customer analysis). However the suite of products is not particularly well integrated, and this is often an annoyance to customers.
Lumira does what many other products do – charts, dashboards, some level of collaboration, and of course it is particularly adept at using SAP data sources and platforms (HANA particularly). In common with some other big BI suite players, customers complain of high prices and, in SAPs case, poor product stability. Of course those organizations that are locked into SAP will just have to grin and bear it, but businesses looking for a platform that supports data exploration, discovery and visualisation are presented with many somewhat more suitable options.
Best Intelligent Interface
SAS Visual Analytics is a taste of where business intelligence, and more broadly, business analytics is heading. It embraces the self-service capabilities that we have all come to expect, but extends this well beyond simple charts and dashboards. Advanced analytics are built-in with the ability to execute ‘what-if’ scenarios, analyze text for sentiment, create forecasts with automatic confidence intervals, and perform predictive analytics if needed. And somewhat unusually for SAS the pricing is reasonable too – five users can be supported for around $8000, although this is clearly aimed at the SMB market.
The ‘legacy’ Enterprise BI offering from SAS is its long established, traditional BI platform, and requires considerable skill to use. This is not the case with SAS Visual Analytics, and users will find a guided, informative, mostly drag and drop interface, capable of creating complex visualizations and performing demanding analysis. Business users will feel at home, and as skills and expectations rise, so SAS Visual Analytics will be able to accommodate.
The ‘rub’ in all of this is that large organizations with sophisticated needs will be lured into adopting other components in the SAS portfolio of products – and by-the-way, what a portfolio – SAS does everything analytics. However, back to the main point, and users might find it just too easy to bring in other SAS products, which in the main are not as easy to use as SAS Visual Analytics, and come with price tags that can make the eyes water. The inability to buy a perpetual license, and very high annual fees are a common cause of complaint in the SAS user community. In fact, if we allow ourselves a certain amount of cynicism, the excellent SAS Visual Analytics could be seen as the lure to bring customers into this somewhat less price competitive product set.
SAS Visual Analytics will be compared with products such as Tableau, but in reality there is no competition. Tableau serves up what has now become a standard menu of charts and dashboards, but does little else (although it has recently adopted support for R). SAS Visual Analytics however is more of a competitor for TIBCO Spotfire, which offers similar advanced capabilities, but does so using a performant implementation of open source R instead of a bespoke language (the language of SAS) – although Spotfire does also support SAS scripts.
Best Speed and Flexibility
Sisense delivers on the promise of self-service business intelligence through its flexible data handling, easy to use interface, and very high levels of performance. These three features work hand-in-hand to make the user experience flow smoothly and quickly. Behind the easy to use interface are some interesting innovations. Most contemporary BI platforms utilize a columnar database for in-memory processing. This is ideal for modest data sets and when data values repeat with a reasonable degree of frequency. However these same databases can struggle when data sets become large (multi-terabyte) and when data values are frequently unique. To overcome these problems Sisense uses what it calls in-chip technology. This makes use of the memory native to contemporary processor chips, which is typically tens of times faster than RAM memory. This enables a fundamentally different approach to data processing, with the result that Sisense can effectively shape data on-the-fly as it processes queries. So large amounts of data do not have to be loaded into memory, which in itself can be a slow process, and the user is free to formulate queries without any preparation of the data.
Sisense 6 will be released near the end of the year and promises to increase the open architecture of the platform, and embrace advanced analytics through an interface with R. The product already supports third party graphics libraries such as D3, and a new ODBC interface will allow third party reporting tools to access Sisense’s very fast database technology. This is a welcome move, allowing Sisense to focus on what it does best, while extending functionality to embrace other BI functions such as production reporting.
Best Advanced Analytics
Spotfire challenges the received wisdom that sophisticated technology is complex, and that easy-to-use technology is unsophisticated. For the large population of business users who simply wish to understand and analyze their data with least possible overhead, Spotfire will oblige. This is particularly true of version 7 where considerable effort has been made to automate routine tasks. However Spotfire goes well beyond routine day-to-day requirements, and as users gain confidence and skills so they can venture into other forms of analytics – statistics, predictive analytics, business rules and optimization, and real-time analytics for processing complex events.
Unlike most of the new generation of data visualization and exploration platforms Spotfire will not present a dead-end as requirements become more complex. And it should be remembered that TIBCO has a long-standing pedigree in technologies which support data, process and application integration – something that is absolutely necessary if businesses want to turn the insights derived from analysis into action.
Tableau Software set the pace for easy-to-use data visualization and exploration software. In practical terms this means business users can get to their data, typically without assistance from IT, and create graphs, charts and dashboards in a way that is most meaningful to them. Authoring takes place on Tableau Desktop which, as a stand-alone environment, can perform its own analysis, either against the Tableau in-memory database, or against external data sources – databases, cloud data sources, spreadsheets and so on. In a group or enterprise setting Tableau Server acts as a central facility for data access, delivering visualizations, enforcing security and managing user access. Tableau Server distributes visualizations through the web browser to almost any device that supports a web browser – desktops and mobile devices.
The architecture of Tableau Server is scalable, and is well demonstrated by the Tableau Public free service where millions of visualizations (albeit simple ones) are served up every day. It does support some level of extensibility, particularly the coding of bespoke applications that are not natively supported, but users have to resort to XML code to achieve this.
One of the more intriguing aspects of Tableau is its integration with the analytic language R. It is such a stark contrast – the easy to use Tableau product set, and the not so easy to use R programming language. Even so it does give advanced users, and programmers the ability to add other forms of analysis into the Tableau environment, and particularly statistical analysis and predictive analytics. This contrasts with some of the competition (Spotfire particularly) who, in addition to an easy to use visualization capability also offer easy to use statistics and predictive analytics tools.
I set out by saying that Tableau set the pace, but in reality it is now at least equalled by several other products. Qlik Sense and Spotfire have both been reengineered for an easy to use experience, and there are cloud based products such as Sisense and GoodData. And of course we should not forget Microsoft’s latest foray into the world of data visualization and exploration with Power BI Designer. It’s immature, but it will be disruptive.
Yellowfin is something of a breath of fresh air in the over-hyped BI market. This is a platform that will address many needs in both large and small organizations, without the pretense that everyone with a display should spend all day playing with charts and dashboards. For those whose job it is to analyze data, Yellowfin provides a rich environment to do such work. For the rest of us who need access to dashboards and reports on an ad-hoc, as-needed basis, it will also provide the information needed.
So all the contemporary features we expect of a BI platform are supported by Yellowfin – charts, dashboards, mobile, maps, big data support, advanced analytics (via R), an in-memory columnar database for speed, multi-tenancy where needed, a semantic (or metadata) layer, strong collaboration features, connectivity to a wide range of data sources, and a web interface so that access is available on all devices with a browser. And all the dull things such as security, scalability and governance are catered for very adequately.
This is also a platform that might appeal to ISVs and those who might want to embed BI into other applications. The mechanisms exist to do these things with relative ease, and of course the multi-tenancy architecture (many distinct groups of users going through the same instance) will be attractive to those wishing to provide BI services in the cloud.
As mentioned in a previous review of Yellowfin, we consider this to be a no-nonsense, get the job done platform, equally capable as many other platforms, but with a more pragmatic approach – a good example being the use of the in-memory columnar database. Many suppliers tout this feature as the cure-all for high speed analytics. It isn’t, and for data that is rich in text or highly variable in content, an in-memory column database may well struggle. Yellowfin is keen to point these issues out, whereas many competitors do not.
This is a BI solution for organizations of all sizes that addresses the needs of a wide variety of users. IT will be happy with the governance features and the ability to set up a semantic layer. Analysts will find the visualization capability more than adequate, and casual users will find they can view dashboards and reports without a great deal of fuss.
Finally it has to be said that because Yellowfin addresses a broad set of needs it does not for example provide the extensive data visualization and exploration capabilities of products such as Tableau, Qlik and Spotfire. However for most business users there is no need to endlessly slide and dice data – most real needs are far more straightforward.