Многолетний опыт, воплощенный в новом бренде
Сегодня рынок ИТ-консалтинга обновляется, и у нас тоже есть новость: компания Columbus East, ранее входившая в состав датской компании, становится независимым международным игроком и меняет свое название. Новый бренд – Odyssey Consulting Group.
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BI on Open Source

In the current environment, business retention and development are determined by how quickly and efficiently management decisions are made. To support this process, modern companies need powerful analytical tools that can quickly give business answers to questions of interest. Such tools were often the platforms and systems of global software vendors. Today they are unavailable to many companies. We have worked out approaches on how to quickly implement all business requirements on modern platforms, free of sanctions risks. Our approach allows not to squeeze your requirements and expectations to the possibilities of less functional platforms, but on the contrary opens new horizons of possibilities due to the use of the most advanced analytical solutions, which have long been developing in the world in the open source concept.

Prerequisites:

  • Departure or threatened departure of global software vendors and the associated lack of ability to buy/replace licenses.

  • Transition to new business applications, including ERP enterprise management systems (domestically produced software, Open Source).

  • Lack of globally competitive data platforms on the domestic market of proprietary BI-systems.

Business problems - lack of analysis tools:

  • Collecting reports in manual mode - time-consuming work of employees.

  • Difficulties of forming full-fledged analytical reports directly by business applications (ERP, CRM, etc.).

  • Collecting and analyzing detailed information (for example, by receipts, by data from the site, equipment, etc.).

  • Difficulty of combining external in relation to the company data with the data of internal information systems (variability of API, formats of providing data, values of analytics).

  • Complexity of processing the volume of historical data, which grows at an explosive rate.

Issues to be worked out when choosing a system:

  • Speed of implementing an analytical solution,

  • Support quality (updates, quick fix, etc.),

  • Minimizing costs - when replacing a large number of systems, it is necessary to keep control of license costs,

  • Provider reliability (scale and breadth of developer community),

  • Performance at the level of data warehouse (DW), processing and providing information,

  • Complexity of staff training,

  • Implementation and support complexity,

  • Business-friendly tools for visualization

Modern technologies of data processing and stack of open source products: all of the above issues need to be considered holistically, but for business it is primarily important to obtain and analyze quality data in time, and for IT, it is important to properly collect, consolidate and promptly publish this data, using available and reliable infrastructure.

Our proposal, built on highly effective open source tools, widely used in the most technologically advanced companies in the world, allows to cover all existing IT and business needs. We offer the implementation of the Analytical Loop based on the following components: [ /upload/medialibrary/bi-na-open-source.png ] Each of the presented tools effectively solves specific application problems in its segment.

From an IT perspective:

  • Data storage. It is important to understand what kind of data the business needs and how to store and process it properly.

For transactional systems:

  • GreenPlum, an advanced version of PostgreSQL with columnar data storage, which provides better performance compared to classic SQL-like databases.
  • HDFS (Hadoop Distributed File System) is used for scalable BigData class data with primary document processing and accumulation.
  • Data processing (ETL). Similarly with data storage, you need to define goals and objectives for ETL. In our proposal, the classic tasks of Talend, streaming data processing (online) and procedural data processing is solved using Apache Kafka and Airflow. Unstructured data is handled by Apache Spark.
  • Storage of processed data. The problem of storing big sparse data is solved with Apache HBase tool developed specially for this purpose.
  • OLAP. As an effective tool for working with big data we offer Kylin - OLAP-tool from Apache based on Hadoop.

From the point of view of business users:

  • Visualization tools: Apache Superset - open source analogue of Power BI with the possibility of creating reports and dashboards. No special programming languages knowledge is required for creating reports, which allows to use it as a self-service-reporting tool.
  • Applied work with the data at the level of "spreadsheets" like Excel - built-in connections to data marts, as well as to the data from Apache Kylin cubes.

These tools are in many ways superior to traditional "BI systems" in functionality and speed, while the "threshold" of entry is much lower:

  • no expensive "license" component;
  • powerful community that develops the solution;
  • no obligatory payments for "support" of the platform;
  • large number of specialists in the market - it is easier to organize your own competence center or entrust the tasks of support and development.

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