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COVER FEATURE
ECOSYSTEM FOR DATA
Lakehouse-Based Data Platform Infrastructure
Analyzing large data volumes enables businesses to greatly improve their operational efficiency. To that end, lakehouse based data platforms are currently used, offering flexibility and scalability by isolating compute from storage. However, no less significant is the infrastructure layer responsible for the platform’s security and component interoperation.
Vladimir Ozerov (vozerov@querifylabs.com), CEO, Querify Labs (Moscow).
Data Maturity at Banks: From Chaos to Data Driven Strategies
Data maturity is not just a multitude of useful technologies and tools, but rather a complex indicator reflecting process maturity, data quality, corporate culture and integration of analytics into decision making. The road to high data maturity is not an easy one—it requires investment, process and mindset changes, as well as modern technology.
Igor Moiseev (i.moiseev@arenadc.io), Business Development Director, Sergey Vasilchikov (s.vasilchikov@arenadc.io), Consulting Director, DataCatalog, Arenadata Group (Moscow).
Data Quality: A Treasure in Itself
Master data management is not just some auxiliary module of an IT infrastructure, but rather a mission critical component of the entire corporate operational model. A project by Mangazeya Mining has demonstrated that even for highly complex structures with tens of thousands of product items, master data can be organized without deploying “heavyweight” IT systems. Thanks to a systemic approach and attention to details, the master data normalization project has become a part of the global process aimed at transforming the company’s data culture.
Tatyana Loginova (t.loginova@mangazeya.ru), Head of Automation, Planning and Inventory Management Department, Mangazeya Mining (Moscow).
Building Efficient Data Office Team
The growing diversity and amount of data are driving businesses to deploy corporate analytics platforms, which in turn calls for a dedicated data office. This creates the need for a team of specialists capable of transforming corporate data culture.
Yaroslav Nazarov (ya.nazarov@marvel.ru), Head of Corporate Data Directorate, Fplus (Moscow).
AI for Manufacturing Master Data
Present-day businesses process millions of records from disparate data sources, with traditional approaches becoming incapable of tackling tasks of that scale. How AI is helping companies in MDM systems implementation and manufacturing information management?
Yulia Sharafutdinova (YSHarafutdinova@inno.tech), Business Analyst, AI Technologies Development Division, T1 AI, T1 Group (Moscow).
PROCESS AUTOMATION
From Automation to Autonomy
Process automation is transforming the approach to business management. How to choose processes that can be made autonomous, and what steps are necessary at the beginning stages? How to build autonomous processes in a way that minimizes risks and helps avoid missteps when trying to automate the chaos?
Mikhail Zyrianov (mikez@osp.ru), Editorial Director, OSP.RU (Moscow)
Process Analytics: a Tool for Improving Business Process Efficiency
With thousands of processes running in large enterprises and impacting operational efficiency, what is the way to discover weak points among them? To address the issue, the Federal Taxation Service of Russia has implemented process analytics based on process and task mining approaches.
Alexander Kotikov (kotikovae@gnivc.ru), head of Process Analytics Directorate, GNIVC.
INTEGRATION
Interactive Assistant Speeds Up Product Launches
The success of digital services businesses depends to a large extent upon a quick period from new idea to minimally viable product and short time to market, as well as upon expanding the scope of innovative ideas and efficiently implementing them in finished products. To achieve those goals, cellular service provider MTS uses the Product Guide navigator that integrates the process lifetime management of its products while enabling it to cut the time to market.
Yekaterina Chugunova (Yekaterina.V.Shestakova@mts.ru), Head of Product Catalog Center, Mikhail Kiselev (makise17@mts.ru), Head of Process Re-Engineering Center, MTS (Moscow).
OPINION
The Last Frontier
In a cyber war, the question is not how much would protection cost, but rather would there still be an ability tomorrow to rule one’s own country.
Mikhail Krikheli (info@itconsortium.ru), Managing Partner, Russian IT Consortium (Moscow).
OS MEETING ROOM
On the Way to Cutting-Edge Analytics
The current geopolitical turbulence is intensifying competition in the logistics services market, forcing companies to rethink traditional pricing models, reassess their service portfolios, cut costs, and continuously search for new routes. As experience of the transportation company PEC has shown, today efficient logistics business is virtually impossible without predictive analytics and AI systems.
Nikolai Smirnov (nsmirnov@osp.ru), freelance writer (Moscow).
OS ACADEMY
Visualization of Digital Repository Data
For visualizing data in the DSpace digital repository using the Chart.js library within the DSpace front-end, built on Angular, a dedicated component and service were developed to render bar charts. A data service was also created to generate the required chart data on the web server through periodic queries to the DSpace database. The component implements adaptive visualization, including mobile device support, while the service handles data retrieval from the server. The article details the architecture, functionality, and implementation aspects of these elements, as well as their role in the context of digital repository data visualization.
Aleksey Bondyakov (aleksey@jinr.ru), Senior Fellow, Andrey Kondratyev (kondratyev@jinr.ru), Junior Fellow, Joint Institute for Nuclear Research (Dubna).
Methodology for Cyber Risk Assessment
As the number of emergencies increases and the Industrial Internet of Things (IIoT) scales up, forecasting cyber threats and assessing information load on distributed systems becomes increasingly critical. This work introduces a methodological approach that quantifies cyber risk and threat parameters while supporting proactive response planning in unstable digital environments. The core of this method lies in using truncated empirical statistics, approximated through the Central Limit Theorem and a two-parameter hyperexponential distribution. This approach effectively captures the high variability and irregular nature of both large-scale and localized incidents, which are typical of cyber and technological threats.
Dmitry Zhmatov (zhmatov@mirea.ru), Alexander Leontiev, Associate Professors, MIREA — Russian Technological University (Moscow).
