Data lake and Data lake Analytics
In this session we start with the importance of building a Data Lake, to nurturing its potential with Hadoop and other analytics options. We go a bit deeper and cover the basic components of the Azure Data Lake Analytics and Azure Data Lake Store.
Patterns of big data applications with a Data Lake Store
In this sessions we discuss various patterns for ingesting data, building big data analytics pipelines and developing applications involving a Data Lake Store. We will also look in to how you can connect various analytics platforms such as Hive, Pig, Spark, R and Azure Data Lake Analytics with data that resides in the Azure Data Lake Store.
U-SQL - Simplifying Big data processing
In this session we will talk about a new language called U-SQL to make Big data processing easy. U-SQL unifies the declarative power of SQL and the extensibility provided by a modern programming language to make writing custom processing of big data easy. It also unifies processing over all data – structured, semi-structured and unstructured data – and queries over both local data and remote SQL data sources.
Abdul Haseeb is currently working in Microsoft as Data Solution Architect. His interests lie in Distributed Fault-tolerant Systems, Big data and Machine learning. His PhD (at KTH) was about dealing with communication Interoperability, and distributed learning for smart devices like robotic swarms.
Erik Gullbring is currently working in Microsoft as a Data Solution Architect with Big Data, Advanced analytics and Machine learning. His PhD was in astrophysics but he is now fully devoted to Big Data solutions.
17.30-17.45 – Meet and Greet
17.45-18.30 – Data lake and Data lake Analytics
18.30-18.50 – Break with something lighter to eat
18.50-19.20 – Patterns of big data applications with a Data Lake Store
19.20-20.00 – Simplifying Big data processing
20.00-......... – Discussion and mingle