The global cloud application market is expected to reach $168.6 billion by 2025. It has rapidly gained traction in the data governance industry due to its cost-effectiveness and simplified data-sharing capabilities. Additionally, the rapid development of AI is poised to significantly transform the entire industry.
We discussed data governance trends and the impact of AI with Alexey Artemov, who is known for his innovative solutions implemented in large corporations such as Magnit, Russian Railways, ALDI, Schwarz Group, and others.
Alexey, whose expertise lies in data governance and solutions architecture across various industries with a focus on retail, believes the industry will undergo a drastic transformation within the next 5 to 10 years.
According to you, the world of data science will drastically change, and you mentioned that retail is one of those industries that can be disrupted. How did your experiences shape your vision towards data governance solutions?
Artemov: Many technical specialists are focused on creating perfect technical solutions. I, on the other hand, always focus on business value and build the implementation process. So, those processes can be changed with the AI revolution.
Throughout my career, I had the opportunity to work on substantial projects for leading companies. For example, At Magnit, Russia's largest FMCG retailer, I implemented a Data Warehouse and analytics system protection, for Russian Railways, I developed the "Corporate Storage and Analytics Platform."
My expertise significantly influenced budgetary decisions for a major Data Project at ALDI, one of the world's top FMCG retailers.
These experiences exposed me to common data challenges that organizations face, especially in data-driven maturity. One significant area I delved into was the intersection of data platforms and data protection.
I observed the gap between information security and data understanding, which inspired me to create approaches for safeguarding data within platforms.
My work in data quality furthered my insights, motivating me to develop a personal project aimed at helping numerous companies enhance their data quality.
Alexey, being a Senior Member of IEEE and part of other prestigious associations like the IEEE Computer Society and the AWS Certified Global Community is quite notable. How has this shaped your journey, and are there other ways besides these associations through which you engage with the professional community?
Artemov: Thank you for acknowledging my memberships. Being a part of these esteemed associations has been instrumental in my professional growth. They've offered me the chance to collaborate with industry leaders, gain insights from cutting-edge research, and also contribute to shaping the technological landscape.
Moreover, outside these associations, I engage with the professional community through conferences, workshops, and mentorship programs. This helps me both in continuous learning and in giving back to the community, ensuring I stay updated and also help nurture the next generation of professionals.
I've always been deeply curious about how things work, right from my childhood. My parents fueled this curiosity with technical toys, which I often dissected to understand their mechanisms. This inquisitiveness led me to pursue Software Engineering, and I eventually earned my master's degree in the field.
During my university years, I found immense joy in participating in student programming contests, where teamwork and problem-solving were paramount. The thrill of collaborative problem-solving and achieving results together ignited my passion for the data industry.
You are one of those specialists who know the retail industry from the inside very well. Can you tell us more about what solutions you previously implemented and how in your opinion, the industry will change?
Artemov: Since 2008, I have been involved in data solutions for the retail industry. It all began with the implementation of a Corporate Data Warehouse solution for Magnit, starting from scratch. I was one of the first two employees working on this project.
Over time, we implemented various solutions on top of our Corporate Data Warehouse.
In April 2017, I was appointed as the project lead for System Access Control and Prevention of Unauthorized Access to Data from the Corporate Data Warehouse and Analytical Reporting Systems. My team conducted audits on access to the Corporate Data Warehouse (Big Data platform) and analytical reporting systems.
We implemented mechanisms to prevent the unauthorized transfer of confidential and strictly confidential data outside the company. At that time, we implemented the best solution available on the market.
It required a significant amount of effort to figure out, but the truth is that the retail industry is becoming more sophisticated every day, dealing with sensitive data of customers, employees, and vendors. The way things were back then is a little different from what is accessible now.
In the project "Data Life Cycle Support," my department was responsible for ensuring the efficient use and storage of data in the Corporate Data Warehouse (Big Data Platform). Under my leadership, regular data inventory was conducted as part of my responsibilities.
Old and unused data was transferred to more cost-effective data storage and processing technologies, resulting in significant savings on equipment for the Corporate Data Warehouse.
This work has been carried out annually since 2015, with savings amounting to hundreds of thousands of dollars per year, making a significant contribution to the IT department's budget.
But technologies are evolving, and you are absolutely right in a sense that AI will absolutely become a game changer in the next 5-10 years for a lot of industries including retail.
Are you currently using AI in your work?
Artemov: I am currently engaged in a groundbreaking project where I am assisting a non-profit organization in establishing an innovative data platform serving Large Language Models (LLMs).
This endeavor involves automation and innovative approaches, aiming to significantly impact people's lives. This project serves as a testament to my commitment to innovative solutions.
Nowadays my approach focuses on crafting solution architectures for data platforms, establishing pragmatic data governance practices, and implementing projects incrementally with a keen eye on business value.
I specialize in aiding companies without the need for extensive external consulting, particularly in areas like Data Catalogs and data quality since I have so much experience.
My extensive experience in the data field, particularly in retail, coupled with profound technical knowledge in building data platforms, gives me a good understanding of what enterprises really need. In my work, I try to emphasize practical solutions and impactful results, derived from years of hands-on experience.
You led the Corporate Data-Competence Center during your tenure at Magnit, organizing and coordinating professional education initiatives for colleagues involved in data analytics and related projects. Did it help you in your career journey?
Artemov: Oh, certainly! I have been actively involved in various industry events, such as the 2023 Data Governance & Data Quality Leadership Summit and the 2022 Smart Data Conference.
Additionally, I have shared my knowledge through articles and educational initiatives. Being part of a community of like-minded people and ability to share knowledge creates that synergy effect that contributes a lot to the industry's evolving.
What do you believe are the biggest challenges for the data industry today?
Artemov: In the data industry, technical challenges like GPU availability for LLM models and standardization in data integration persist.
However, the most significant hurdles are non-technical, involving reliance on source systems and lack of efforts from source system developers to enhance their tools, leading to challenges in Data Quality and Data Governance.
Additionally, the industry faces difficulties in managing the plethora of tools and frameworks.
According to you, the world of data science will drastically change, and you mentioned that retail is one of those industries that can be disrupted. How did your experiences shape your vision towards data governance solutions?
Artemov: My experiences working on large-scale data projects for major companies like Magnit, Russian Railways, and ALDI, Schwarz have given me a firsthand perspective on the common data challenges organizations face, particularly in terms of data-driven maturity.
One of the key areas I focused on was the intersection of data platforms and data protection. I observed a significant gap between information security and data understanding, which motivated me to develop approaches for safeguarding data within platforms.
My work in data quality furthered my insights, driving me to create a personal project aimed at helping numerous companies enhance their data quality.
You mentioned the importance of data governance in the retail industry. Can you elaborate on the specific benefits that retailers can reap from effective data governance practices?
Artemov: Data governance plays a crucial role in ensuring that retailers can effectively manage and utilize their data assets to drive business growth. By implementing robust data governance practices, retailers can do several things.
First, to enhance data quality and reliability: Data governance ensures that data is accurate, consistent, and complete, enabling retailers to make informed decisions based on reliable insights.
Second, improve data accessibility and usability. By establishing clear data ownership and access policies, retailers can make data more readily accessible to authorized users, fostering a data-driven culture across the organization.
Third, minimize data security risks: Effective data governance practices help protect sensitive customer, employee, and vendor data from unauthorized access, theft, or breaches, ensuring compliance with data privacy regulations.
What advice would you give to aspiring data professionals who want to make a meaningful impact in the retail industry?
Artemov: For aspiring data professionals seeking to make a significant impact in the retail industry, I would recommend: first, develop a deep understanding of the retail business: Gain a comprehensive understanding of the retail industry, its challenges, and its opportunities. This will enable you to identify and address specific data-related issues that can make a real difference for retailers.
Secondly, master data science and data engineering skills: Acquire strong data science and data engineering skills to effectively collect, analyze, and interpret data, transforming it into actionable insights for retailers.
Third, become a data storyteller: Develop effective communication skills to translate complex data findings into clear and compelling narratives that resonate with business stakeholders.