Evaluation Criteria for Russian BI Systems

For many years I have been leading a company that is one of the leaders in the implementation of BI-systems in Russia and is regularly included in the top lists of analysts by volume of business in the field of BI. During my work, I participated in the implementation of BI-systems in companies from various sectors of the economy - from retail and production to the sports industry. Therefore, I am well aware of the needs of customers for business intelligence solutions.

The solutions of foreign vendors are well known, most of them have a strong brand, large analytical agencies analyze their prospects, then domestic BI-systems for the most part remain niche products. This seriously complicates the choice for those who are looking for a solution to satisfy their needs.

To eliminate this drawback, we with a team of like-minded people decided to review the BI-systems created by Russian developers - “Gromov's BI Circle”. We analyzed most of the domestic solutions presented on the market and tried to highlight their strengths and weaknesses. In turn, the developers of the systems included in the review, thanks to him, will be able to look from the pros and cons of their products from the side and, possibly, make adjustments to their development strategy.

This is the first experience in creating such a review of Russian BI-systems, so we focused on collecting information about domestic systems.

A review of Russian BI-systems is carried out for the first time, its main task is not so much identifying leaders and outsiders as collecting the most complete and reliable information about the possibilities of solutions.

The review was attended by decisions: Visiology, Alpha BI, Foresight. Analytical platform, Modus BI, Polymatica, Loginom, Luxms BI, Yandex.DataLens, Krista BI, BIPLANE24, N3.ANALITIKA, QuBeQu, BoardMaps of Dashboard Systems OJSC, Slemma BI , KPI Suite, Malahit: BI, Naumen BI, BEACON BI, IQPLATFORM, A-CUB, NextBI, RTAnalytics, Simpl. Data Management Platform, DATAMONITOR, Galaxy BI, Etton Platforms, BI Module



To analyze the functionality and architectural features of Russian BI platforms, we used both internal data provided by developers and open sources of information - solution sites, advertising and technical materials of suppliers.
Analysts, based on their own experience in implementing BI-systems and the basic needs of Russian companies in BI-functionality, identified a number of parameters that allow us to see the similarities and differences of solutions, and subsequently to highlight their strengths and weaknesses.

These are the parameters

Administration, security, and architecture of the BI platform - in this category, we evaluated the availability of a detailed description of the features that ensure the platform’s security, as well as the functionality for user administration and access auditing. The total amount of information about the platform architecture was also taken into account.

BI Cloud - this criterion allows you to evaluate the availability of connectivity using the Platform as a Service and Analytic Application as a Service models for creating, deploying and managing analytical and analytical applications in the cloud based on data both in the cloud and locally.

Connect to a source and receive data- the criterion takes into account the capabilities that allow users to connect to structured and unstructured data contained in various types of storage platforms (relational and non-relational) - both local and cloud.

Metadata management- takes into account the availability of descriptions of tools that allow the use of a common semantic model and metadata. They should provide administrators with a reliable and centralized way to find, capture, store, reuse, and publish metadata objects such as dimensions, hierarchies, metrics, performance metrics, or key performance indicators (KPIs), and can also be used to report on layout objects. , parameters, etc. Also, the functional criterion takes into account the possibility for administrators to promote data and metadata defined by business users into SOR metadata.

Data storage and loading- This criterion allows you to evaluate the capabilities of the platform for access, integration, conversion and data loading into an autonomous performance mechanism with the ability to index data, manage data loading and update schedules. It also takes into account the availability of functionality for deployment on an extranet: does the platform support a workflow similar to flexible centralized initialization of BI for an external client or citizen access to analytical content in the public sector.

Data preparation- the criterion takes into account the availability of functionality for “dragging” a user-controlled combination of data from various sources and the creation of analytical models, such as user-defined measures, sets, groups and hierarchies. Enhanced capabilities within this criterion include semantic autodiscover capabilities with support for machine learning, intelligent combining and profiling, hierarchy generation, distribution and mixing of data in various sources, including multi-structured data.

Scalability and complexity of the data model- the parameter evaluates the availability and completeness of information about the internal memory mechanism or architecture in the database, thanks to which large amounts of data are processed, complex data models and performance optimization and deployment of a large number of users occurs.

Advanced analytics - the availability of data on the functionality was assessed, which allows users to easily access advanced offline analytical capabilities using menu-based options or by importing and integrating externally developed models.

Dashboards- this criterion takes into account the availability of a functional description for creating interactive dashboards and content with visual research and built-in advanced and geospatial analytics, including for use by other users.

Interactive visual research - evaluates the completeness of information about the functionality for researching data using a variety of visualization options that go beyond the basic pie and line diagrams, including heat and tree maps, geographic maps, scatter charts, and other special visual images. It also takes into account the ability to analyze and manipulate data, directly interacting with their visual representation, displaying them in the form of percentages and groups.

Advanced Data Discovery- in this criterion, the availability of functionality for automatically finding, visualizing and reporting important definitions, such as correlations, exceptions, clusters, links and forecasts in data that are relevant to users, without requiring them to build models or write algorithms, was evaluated. It also took into account the availability of information about the possibilities for studying data using visualizations, narrative technologies, search and natural language queries (NLQ).

Functionality on Mobile Devices- This criterion takes into account the availability of functionality for the development and delivery of content to mobile devices for the purpose of publication or study in an interactive mode. It also evaluates data on the use of native capabilities of mobile devices such as touch screen, camera, and location.

Embed analytic content- this criterion takes into account the availability of information on a set of software developers with APIs and support for open standards for creating and modifying analytical content, visualizations and applications, embedding them in a business process, application or portal. These capabilities can be located outside the application, reusing the analytic infrastructure, but should be easily and unobstructed from within the application, without forcing users to switch between systems. This parameter also takes into account the availability of integration capabilities of analytics and BI with the application architecture, which allow users to choose where analytics should be embedded in the business process.
Publishing and collaborating in analytic content — The criterion takes into account the capabilities that allow users to publish, deploy, and use analytic content through various types of output and distribution methods that support content search, scheduling, and alerts.

Ease of use, visual appeal and integration of the workflow - this parameter overall assesses the availability of information about the ease of administration and deployment of the platform, the creation of content, the use and interaction with content, as well as the degree of attractiveness of the product. It also takes into account the extent to which these features are offered in a single seamless product and workflow, or in multiple products with little integration.

Presence in the information space, PR - criterion evaluates the availability of information about the release of new versions and completed projects in open sources - in the media, as well as in the news section on the product or developer’s website.