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DATA QUALITY
Data Quality: from Strategy to Practice
Neither huge data amount, nor AI technology would be of help to organizations relying upon data that contain errors. In order to turn terabytes of raw data into business assets or necessary services, an enterprise data quality management system is necessary.
Dmitry Volkov (vlk@keldysh.ru), fellow, Keldysh Institute of Applied Mathematics; Alexei Neznanov (aneznanov@hse.ru), fellow, Higher School of Economics - National Research University (Moscow).
Master Data Restructurization
The quality of master data is vital when it comes to procurement efficiency at a business sensitive to losses due to unreliable data. However, normalization of massive data amounts is a non-trivial challenge.
Konstantin Rybakov (krybakov@kpmg.ru), Alla Tokareva (AllaTokareva@kpmg.ru), MDM area manager, procurement and supply chain consulting group, KPMG (Moscow).
PLATFORMS
OpenGL for Mission-Critical Systems
The article covers the process of development and certification of an OpenGL library for safety-critical systems, primarily for aircraft avionics. While the implemented OpenGL SC library simplifies system certification, the desired performance is achieved not for all applications. An implementation of a MESA driver for JetOS successfully addresses the performance issues.
Boris Barlandian (bbarladian@gmail.com), Alexei Voloboy (voloboy@gin.keldysh.ru), Vladimir Galaktionov (vlgal@gin.keldysh.ru), Lev Shapiro (pls@gin.keldysh.ru), fellows, M. V. Keldysh Institute of Applied Mathematics (Moscow).
Smart Edge: The Effects of Shifting the Center of Data Gravity Out of the Cloud
A confluence of macrotrends is pushing data, computing, and analytics into the rapidly expanding world at the edge of the connected ecosystem. What is shifting, what is causing it, and what are the overall effects?
Marc Campbell (MCampbell@trace3.com), chief innovation officer, Trace3.
IT MANAGEMENT
Evaluating Maturity of Business Process Management System
A digital transformation project would never achieve success without a well-established business process management system, with the company having the most efficient processes in an otherwise level playing field poised to win.
Vladimir Repin (info@bpm3.ru), management consultant, member of ABPMP Russian Chapter (Moscow).
ARTIFICIAL INTELLIGENCE
Using Video Analytics to Measure Service Quality
The praise of e-government services by a state’s residents is the best indication of a successful digital state project. That is why it is critical to automate providing objective information about the level of satisfaction of an e-government center’s visitors.
Vladimir Soloviev (vsoloviev@fa.ru), head of data analysis, decision-making, and financial technology department, Financial University under the Government of the Russian Federation (Moscow).
INTEGRATION
Excel vs. Business Analytics
Should a business analytics system be used by your organization, or just Excel would be enough? This is no idle inquiry: despite the success of using business analytics for getting insights based on corporate data, Excel sheets are far from losing their popularity. Which way should be analytics infrastructure built in order to address most required tasks without much overhead?
Ivan Vakhmianin (ivan@visiology.com), CEO, Visiology (Moscow).
SECURITY
The Smart and Dangerous Internet of Things
With the Internet of Things becoming a sweet spot for hackers by turning into a source of new cyberthreats, the situation necessitates additional efforts aimed at minimizing the risks and creating a set of security standards.
Dmitry Pudov (pudov@angaratech.ru), deputy CEO for technology and development, Angara Technologies Group; Nikita Andreyanov (n.andreianov@ngrsoftlab.ru) Dataplan platform architect, NGRSOFTLAB (Moscow).
SOFTWARE ENGINEERING
Data Science: Technologies for Better Software
Data science is rapidly gaining relevance among software teams. Data science methods facilitate analyzing and predicting different quality aspects of the software product, process, and use by combining results from different data sources, such as versioning systems, issue-tracking systems, and static code analysis, in an efficient way.
Christof Ebert (christof.ebert@vector.com), managing director, Vector Consulting Services; Jens Heidrich (jens.heidrich@iese.fraunhofer.de), division manager, Silverio Martinez-Fernandez (silverio.martinez@iese.fraunhofer.de), researcher, Adam Trendowicz (adam.trendowicz@iese.fraunhofer.de), senior consultant, Fraunhofer Institute for Experimental Software Engineering IESE.
How to Select Open Source Components
With millions of open source projects available on forges such as GitHub, it may be difficult to select those that best match your requirements. Examining each project’s product and development process can help you confidently select the open source projects required for your work.
Diomidis Spinellis (dds@aueb.gr), professor, Athens University of Economics and Business.
DATA ACADEMY
Corporate University for the Digital Transformation Era
Head of a corporate university at cellular operator MTS talks about the ways approaches to corporate training change these days, including due to the digitalization trend.
Irina Sheyan (rrisha@osp.ru), reviewer, Open Systems.DBMS Journal (Moscow).
OPINION
RPA: What, Where, for Whom?
The current hype around robotic process automation tools creates both positioning challenges for them and issues with choosing ways to address specific business tasks. Where and how RPA would work best and what is the technology’s potential in Russia?
Alexander Beider (www.terralink.ru/rpa), RPA area manager, TerraLink (Moscow).
LIBRARY
What Happened, what is to Happen: Reviews and Forecasts
The December, January, February issues of Computer Magazine offer technology predictions, as well as cover the subjects of technological diversity and digital healthcare.
Andrei Nikolayenko (ANikolaenko@Ibs.ru), architect, IBS (Moscow).
