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COVER FEATURE
PROCESS MANAGEMENT
Process Architecture Modeling Notations
With several architecture modeling notations existing, the choice between them is a non-trivial task. For instance, the currently most popular BPMN notation is well-suited for modeling certain business processes, but it cannot be used for visualizing an organization’s “birdseye” business process map. How to navigate notations when selecting tools for modeling an organizational process architecture?
Anatoly Belaichuk (bell@b-k.ru), President, ABPMP Russian Chapter; Ilya Tomoradze (ilya@ranepa.ru), Assistant Professor, Russian Presidential Academy of National Economy and Public Administration (Moscow).
Why Doesn’t the Process Approach Work?
Despite Business Process Management being a well-established field, many companies still struggle to make the process approach work: a detailed BPMN description has no effect, strict process specification fails to produce results, while ordinary business process performers often ignore the process approach, with their motivation growing into the most pressing issue.
Vladimir Repin (info@bpm3.ru), Management Consultant, Process Architect and Methodologist; Mikhail Ermolayev (info@gab.kz), Change Management Expert, Organizational Development Consultant, Managing Partner, GAB; Roman Agzamov (agzamovroman1993@gmail.com), Business Process Digitalization Specialist, Head of Digital Engineering and Processes Department, VSM Service (Moscow).
DATA MANAGEMENT
Data Quality Assurance Processes
Implementing continuous data quality assurance is not only an IT task, but a fundamental process ensuring the resilience of a financial organization and spanning all of its departments.
Anastasiya Zaytseva (ZaytsevaAG@mkb.ru), Head of Department for the Development and Implementation of Data Management and Quality Assurance Practices (Moscow).
Integrating Data Quality Management into Business Processes
What is the effect of the Data Quality by Design approach and what important aspects should be accounted for when implementing it in an organization? Leading data quality management market experts talk about the role of integrating the discipline into business processes to improve efficiency, accelerate management decision making and lower operational risks by avoiding the use of low-quality data.
Mikhail Zyrianov (mikez@osp.ru), Editorial Director, OSP.RU (Moscow).
Data Product Quality: Data Governance and DataOps
Despite data being the basis for success of a digital business, almost half of data turns out to be unusable. Without a systemic approach to data management, data gets distorted at every stage of its lifecycle. As a result, data products lose the trust of the business. Development process synergy and data governance can remedy the situation. How to implement those and why don't traditional approaches work?
Pavel Egorov (pv.egorov@jet.su), Big Data Discipline Head, Jet Infosystems (Moscow).
Scaling Data Management Processes when Transitioning to Microservices Architecture
When using a single data store, the quality assurance processes are concentrated around that store, but when replacing several monolithic systems with hundreds of microservices, this approach turns out to be non-viable.
Svetlana Bova (bova@vtb.ru), Chief Data Officer, IT Architecture Department Managing Director, Vice President; Rostislav Dankov (rdankov@vtb.ru), Data Quality Management Project Manager, IT Architecture Department, VTB (Moscow).
DBMS
Critical Infrastructure Data Protection
Technology sovereignty means that critical infrastructures utilizing restricted-access information must use locally developed databases guaranteeing proper data protection from both external and insider attacks. The choice of a database for restricted-access information is currently largely determined by regulations: it must have cryptography mechanisms, hardened protection at every data storage and processing tier, as well as performance and integrity monitoring. The Red Database complies with the requirements of Russia’s Federal Service for Technical and Export Control while offering additional critical infrastructure protection capabilities.
Roman Simakov (roman.simakov@red-soft.ru), Deputy Director of Systems Software Division, RED SOFT (Moscow).
Analytical Databases for Critical Information Infrastructure
Once data became the fuel of the digital economy and the main target of hackers' attacks, it became clear that any cybersecurity perimeter would be vulnerable if the systems' software was protected with bolted-on tools rather than at the architectural level. The security technologies of the Russian analytical databases RT.Warehouse and RT.WideStore have been embedded in the database engine architecture from the ground up.
Nikita Bogdanov (nikita.bogdanov@tdata.tech), Database Discipline Head, TData (Russia).
OPINION
Efficiency During Change
In most industries, three factors currently have become more influential: uncertainty, market intolerance for long IT solution deployment cycles, and sensitivity to latency. As a result, efficiency does not come just to the traditional cost optimization: it is also viewed as an ability of a business to achieve results despite harsh restrictions. This transformation clearly manifests in digitalization projects, where corporate management models lag behind in adjusting to speed and cost requirements. However, the efficiency principles typical of IT projects are applicable to other industries as well, such as manufacturing, services, logistics, sales, government, and more.
Alexander Tyutyunnik (atutunnik@luxms.ru), Business Development Director, Luxms Group (St. Petersburg).
How to Overcome the AI Scaling Barrier
Most artificial intelligence implementation projects remain at the pilot stage. This is due to the lack of a systematic approach to data management and a comprehensive AI implementation strategy.
Dmitry Krasnikov, Head of Big Data & BI, K2Tech (Moscow).
OS ACADEMY
IT Specialist Training Ecosystem for Scientific Projects
Sooner or later, any organization faces a shortage of highly skilled personnel, especially for non-standard tasks; yet university academic programs often lag behind the requirements of present-day scientific centers. As a result, scientific research institutions now have to train IT specialists for major projects themselves. Russia’s Joint Institute for Nuclear Research is no exception.
Vladimir Korenkov (korenkov@jinr.ru), Daria Pryahina (pryahinad@jinr.ru), Oksana Streltsova (strel@jinr.ru), IT Lab staff members, Joint Institute for Nuclear Research (Dubna).
Universal Cloud Storage Access
Provider-specific APIs are used to access various types of cloud storage, and there is no way to get universal access to private, public and hybrid clouds. The situation calls for an expandable library supporting universal cloud access that enables connections to any type of cloud infrastructure.
Lyudmila Lvova (lvovalm13@gmail.com), postgraduate student; Kirill Bogachev, professor, Faculty of Mechanics and Mathematics, M. V. Lomonosov Moscow State University (Moscow).
