WEBINAR
From raw data to insights: Effective data processing techniques
This webinar was live on 25th of May at 8:30 PST.
Modern data engineering supporting data-heavy businesses
In this upcoming webinar, we will look inside the most critical areas of data engineering (DE) and how they relate to networking, cloud, security, and monitoring. Our team of experts will showcase several use cases of DE, including data architecture modeling and the decision-making process involved in creating a relevant business solution.
Thanks to this webinar, you will learn more about:
- Processing of large data sets.
- Cost-effective and time-saving solutions for data preparation before AI/ML processing.
- Practical insights into how data engineering can be applied to real-world problems.
Agenda
- Introduction to data engineering
First, we will cover a range of topics related to data engineering and its role in networking, cloud, security, and monitoring. Then, we will introduce you to DE, followed by a reference to our webinar on AI/ML applications for networks.
- Selected use cases of data engineering
Next, we will explore several use cases of DE, including data architecture modeling and designing solutions tailored to specific business use cases. We will also show the processing of large data sets, offering tips for achieving a cost and time-effective outcome. Then, we will cover the steps of data preparation, such as cleaning, normalization, enrichment, and shuffling, which are necessary before AI/ML processing or choosing the best ML model.
- Summary of key aspects
Finally, we will sum up the webinar and review how DE can help you unlock the full potential of your data, plus how to choose the best ML model and implement strategies.
- Q&A
During the Q&A session, we will answer any questions you may have. Take part to learn more from industry experts and discover how DE can help your business grow.
About the speakers
Tomasz Jędrośka - Head of Data Engineering
Tomasz is the Head of the Data Engineering department at CodiLime, responsible for setting up and maintaining collaboration with customers and providing them with advice on the data architecture design relevant to their business case. Along with his professional responsibilities, he is an avid volleyball player and loves to take cross-country cycling trips.
Łukasz Rogalski - Senior Software Engineer
Łukasz is a Senior Software Engineer and Technical Lead at CodiLime, currently focusing on big data and business intelligence systems. In his spare time, he enjoys cooking and working out.
Katarzyna Hewelt - Data Scientist
Kasia is a Data Scientist at Codilime with a strong skill set in machine learning and NLP and a developing passion for large language models. Outside of work, she enjoys sports and staying active.