The Advanced Analytics Survey is a brand new BARC research study focused on the advanced analytics software tools market. Our research is primarily based on a major survey of 677 software users and consultants worldwide, and provides a wealth of user feedback on ten of the leading advanced analytics solutions on the market today.

Our user survey covered issues ranging from the selection and purchase of software through to deployment and use, including questions about the success of software projects, the usability of each product and the challenges encountered.

The following links provide more detail on our survey methodology, the survey sample, and how we categorize and score advanced analytics products:

Sample, Products, Methodology & KPIs
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Respondents
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Advanced Analytics Products
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Components of The Advanced Analytics Survey

The findings from The Advanced Analytics Survey are presented in a number of documents (see below). They do not need to be read in sequence. ‘The Results’, and the ‘Vendor Performance Summaries’ can be read independently.

The Advanced Analytics Survey Analyzer, a web-based, self-service tool enables users to carry out their own analysis of the survey results.

The Results

An overview and analysis of the most important product-related findings and topical results from The Advanced Analytics Survey 19.

The Analyzer

Our powerful interactive online tool, enabling you to perform your own custom analysis of the full survey data set.

Vendor Performance Summaries

A series of reports on each of the products featured in The Advanced Analytics Survey 19. Each report contains an in-depth product review by BARC’s analyst team plus all the relevant product-related results from The Advanced Analytics Survey.

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Sample & methodology

Much of the value of The Advanced Analytics Survey lies in the large number and distribution of survey responses. With a sample of 677 responses, it is among the largest independent surveys into this topic in the world.

This section describes the characteristics of the people who took part in the study, including information on the type, company size and industry sector of participants.

The sample of the Planning Survey

Sample size and make-up

Many thousands of people were invited to take part in The Advanced Analytics Survey 19, using a range of media.

A summary of the online data collected is shown in the table, with the number of responses removed also displayed.

Our data cleansing rules are thorough and involve several different tests. All fraudulent or suspect data that purports to be from bona fide advanced analytics software users is removed.

The number of responses is divided between users, consultants and vendors. The questionnaire for vendors contains a different set of questions to those answered by users and consultants.

Responses removed from the sampleResponses
Total responses687
Removed during data cleansing-10
Total answering questions677
Breakdown of responsesResponses
Users386
Consultants110
All users496
Vendors/Resellers70

Organization sizes by headcount

Advanced analytics products are mostly found in large organizations, a fact reflected in the high percentage of responses we received from users in companies with more than 2,500 employees.

However, the level of responses from mid-size organizations (100 – 2,500 employees) was not far behind on 36%. Participants from smaller companies (i.e., with less than 100 employees) formed the smallest grouping with 21% of the total number of responses.

The distribution of the Advanced Analytics Survey by company size

Frequency of employee count in respondent organization (n= 389)

Vertical markets

The chart on the right shows the breakdown of survey responses by industry sector. It only includes respondents who answered product-related questions in the survey (i.e., users and consultants).

The services industry tops the list with 24% of the sample, followed by manufacturing with 19%.

Advanced Analytics Survey respondents analyzed by industry

Respondents analyzed by industry (n=582)

Products in The Advanced Analytics Survey

10 advanced analytics tools are analyzed in detail, having reached the inclusion threshold of 20 user reviews each.

For convenience, the product names we use in The Advanced Analytics Survey are sometimes abbreviated and are not always the official product names used by the vendors at the time of publication.

We asked respondents explicitly about their experiences with products from a predefined list, with the option to nominate other products.

Where respondents said they were using an ‘other’ product, but from the context it was clear that they were actually using one of the listed products, we reclassified their data accordingly.

The table to the right shows the advanced analytics products included in our detailed analysis.

Product
Alteryx
Dataiku
IBM SPSS/WS
IBM SPSS/WS/CA
Microsoft Azure/SQL Server
Microsoft Power BI
Qlik
Rapidminer
SAS
Tableau

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The peer groups

The Advanced Analytics Survey 19 features a range of different types of advanced analytics tools so we use peer groups to help identify competing products. The groups are essential to allow fair and useful comparisons of products that are likely to compete.

The peer groups have been defined by BARC analysts using their experience and judgment, with segmentation based on usage scenario. These functional peer groups are mainly data-driven and based on how customers say they use the product.

Peer groups are intended to help the reader understand which products are comparable and why there is such a disparity of findings between all the individual products. The groupings themselves make no judgment on the quality of the products. Most products appear in more than one peer group.

Advanced analytics is a generic term for analysis based on mathematical models. Its aim is to identify relationships between variables in order to derive insights from existing data (patterns) as well as new data (forecasts). This peer group contains advanced analytics platforms that provide a broad range of algorithms. They also offer data preparation and visualization functionality, together with options for model deployment.

Data discovery is the business user/analyst driven process of discovering patterns and outliers in data. This peer group includes products that focus on all the sub-elements of data discovery: data preparation, visual analysis and guided advanced analytics.

Data preparation is the process of cleaning, structuring and enriching data for use in data discovery and/or advanced analytics. This peer group includes products and vendors that support these tasks.

The ‘Software generalists’ peer group includes products which are part of a vendor‘s broader business software portfolio. Customers that standardize on such vendors may be more inclined to select their standard provider’s solutions.

The KPIs

The KPIs are designed to help the reader spot winners and losers in The Advanced Analytics Survey 19 using well-designed dashboards packed with concise information. There is a set of 22 normalized KPIs (which we refer to as ‘root’ KPIs) for each of the 10 products, as well as 6 aggregated KPIs based on aggregations of various combinations of ‘root’ KPIs.

A set of KPIs has been calculated for each of the seven peer groups. The values are normalized according to the whole sample.

The KPIs all follow these simple rules:

  • Only measures that have a clear good/bad trend are used as the basis for KPIs.
  • KPIs may be based on one or more measures from The Advanced Analytics Survey.
  • Only products with samples of at least 15 to 30 (depending on the KPI) for each of the questions that feed into the KPI are included.
  • For quantitative data, KPIs are converted to a scale of 1 to 10 (worst to best).
  • A linear min-max transformation is applied, which preserves the order of, and the relative distance between, products‘ scores.
  • In some instances, adjustments are made to account for extreme outliers.

KPIs are only calculated if the samples have at least 15 to 30 data points (this varies depending on the KPI) and if the KPI in question is applicable to a product. Therefore some products do not have a full set of root KPIs.

Our methodology document describes all the KPIs and calculation methods in detail. See our methodology PDF.

Aggregated KPIsRoot KPIs
AnalyticsData preparation
Data visualization
Visual analysis
Advanced analytics breadth
Business valueBusiness benefits
Project success
Project length
Customer satisfactionProduct satisfaction
Vendor support
Implementer support
Price-to-value
Recommendation
Data managementPerformance satisfaction
Data volume
Data variety
Governance
OperationalizationModel scoring
Model management
User experienceEase of use
Code-free usage
User guidance
Collaboration
Openness