Data utilization becomes one of the critical competitive advantages for modern companies. According to the International Institute for Analytics, by 2020, data-driven companies will bypass competitors who do not use data to make decisions by any less than $430 billion.
This course is aimed to provide a clear understanding of:
data collection and aggregation,
validation and storing,
data governance and processing required data to ensure the accessibility, reliability, and timeliness of the data for its users.
The course is built on a carefully selected mix of teaching methods, lasts for a month and consists of 2 blocks of lectures/workshops.
After the successful completion of the course, the participants will get a certificate.
After completing the course you’ll be able to:
Identify data needed to be collected for a particular business case and easily distinguish various data types;
Understand what data management is and why it is essential for any modern organization;
Create a relational database schema;
Understand how to design data warehouses and business intelligence systems;
Understand the principles of data profiling, data integration, data governance, and master data management;
Asses different data architectures in the context of business requirements;
Understand the basics of SQL, NoSQL, distributed, and hybrid architectures.
Entrepreneurs and business owners, who want to recognize data opportunities and utilize data analysis in their business, professionals who want to help their organization grow with data-driven decisions.
Requirements for students:
Price: UAH 24 000, including VAT
25 Oct. 9 am – 1:20 p.m (6 hours)
Introduction to DM. Types of data. Databases. DBMS. Overview of SQL, NoSQL, HDFS, cloud storage.
26 Oct. 9 am – 1:20 p.m (6 hours)
Data governance. Data strategy. Metadata.
27 Oct. 9 am – 1:20 p.m (6 hours)
Data model. DB design. Data architecture. DWH, data vault, data lake. Hybrid architecture.
8 Nov. 9 am – 1:20 p.m (6 hours)
DB administration. ETL and ELT. Data pipeline.
9 Nov. 9 am – 1:20 p.m (6 hours)
Master Data Management. Data lifecycle. Business Intelligence. Data integration.
10 Nov. 9 am – 1:20 p.m (6 hours)
Data-driven decision-making. Group cases presentation.