Content and procedure
Data-intensive applications need a sophisticated data architecture more than ever before. Finally, the data world is more versatile and voluminous than ever. In addition, Analytics projects are constantly struggling with the challenge of data acquisition and processing, which is often a brake on agility and motivation at the same time. Therefore, a carefully designed data architecture with deliberately applied design principles quickly pays off. The workshop will discuss the following questions:
- The data-centric enterprise - why a data architecture?
- What distinguishes the data warehouse from Data Lake, which common data architecture approaches are used and what role do they play from the point of view of analytics?
- What data types are there, such as transactional versus machine-generated data such as weblogs and JSON formats, and how does their use differ?
- What are the most common data stores (e. g. relational versus NoSQL) and access mechanisms?
- How are raw data prepared for different use/evaluation types? What is the difference in the processing from historical to real-time data?
- How to secure data (re-)usability for business analysts, BI experts and data scientists?
- What are the challenges of a distributed data architecture?
- What do you need to consider if you want to turn a prototype data pipeline into an operational and scalable application?
The conceptual approaches discussed in the workshop will be illustrated with practical examples.
- Trainer: Jacqueline Bloemen
- Language: German
- 16th of April 2018
- 10:00 – 17:15
- Data Hub, Sapporobogen 6-8, 80637 München
Design the data architecture according to requirements
Use data type- and task-oriented methods and technologies
Design (re)usable data objects
Being able to implement strategies for solving key data challenges
is a senior analyst and advises national and international companies of various sizes and industries in the areas of strategy definition for business intelligence, data warehousing, big data analytics and digitalization, architecture conception, data architecture and modeling, solution design, software selection and development, as well as overall strategy and organizational development in the age of digitalization. She has been working for BARC since 2005.
10:00 – 11:15: Data architecture concepts for digital companies
11:15 – 11:30: Coffee break
11:30- 13:00: Data types, data storage, data models – how it works together
13:00 – 14:00: Lunch break
14:00 – 17:15: From raw data via analytics to operationalization – a practice-oriented, exemplary target image
The workshop is aimed at Data Engineers and Data Scientists, Enterprise and BI/Analytics Architects as well as Technology-Affine Data Stewards, BI Power Users and Business Analysts.