Data Management Lab

Head of Laboratory: Azat Yakupov

Address: 420008, Kazan, 35 Kremlevskaya street, office 1411.

E-mail: azat.yakupov@it.kfu.ru

About me:

I am a graduate of Kazan Federal University at 2004 by speciality “Mathematical methods in Economy”.

My official certifications paths for different aspects in the databases

- Oracle Database Performance Tuning Certified Expert

- Oracle Advanced PL/SQL Developer Certified Professional

- Oracle Application Express Developer Certified Expert

- Oracle Database Administrator Certified Associate

- MS SQL Server MCP

I am IT architect and data engineer for high loading and high availability systems of databases, processing relational and weakly structured of data 

I have a great and huge experiences to work with databases in production systems and I want to share my knowledge between my students.

My goal in DataLab is to create friendly group of motivated students to learn different aspects to work with data in different types of databases.

Laboratory's collaborators: 

Roman Tretyakov (The Central Bank of the Russian Federation)

Main message: 

In modern digital world namely world of huge data exchanges - there is an important and main question about data, how data store in the best way during system creation / system support and further data analysis.

Major Aspects of Laboratory:

• Big Data Engineering
• Analysis of data structure and data content to improve TPS metric for particular business model 
• Analysis of big volume of data to take statistical correlations, to find common patterns in data for further analysis
• Algorithms of data structures, investigations and improvements of particular business cases to use in search engines
• Analysis of existing business models to find the best ways for data distributions and improve TPS metrics for search queries
• Relational Database Management Systems
• noSQL databases
• In-Memory databases
• Weakly structured models and databases
• Data Lakes / Data Vaults  and taxonomy model
• Data Mining
• Data Analysis and Data Statistics
• Streaming and queue of data
• Data integration for different types of databases
• Lambda architecture for data structures and data storages
• Online / Offline data encryption and data obfuscation for huge amount of data
• Probabilistic models to use in search requests for huge amount of data

Student's work and researches

Practice and researches are based on individual / team projects with resources of Amazon Cloud

Laboratory's and additional courses

• Introduction into Relational Databases
• Data Warehouse Management Systems
• Advanced Relational Databases
• Data Analysis and Data Mining

Achieved Skills and Expertises:

• Big Data Database Engineer
• Database Architect Engineer
• Data Engineer
• Data Analyst
• Data Integration Engineer
• Performance Tuning Engineer
• SQL Engineer
• Database DevOps Engineer
• Database Balancer Engineer

Our partners: