Join us every Wednesday at 1pm EDT
As a technology professional, your success is predicated on having a well thought out data strategy to drive your business. You are on your transition from rigid data warehouses that are cost-ineffective and cannot keep pace with changing business needs. Many organizations start down the same path and the decisions they make early on become limiting factors.
Join Informatica for this five-part series, where we'll walk you through the steps to take as you embark on your data lake journey - from origin to insights. We will also highlight how organizations can leverage cloud ecosystems and avoid the pitfalls of vendor lock-in.
Below you will find the list of dates and the data lake framework stages that we will feature. Each session will be recorded. Register once to participate in all 5 of the series sessions.
Part 1: Raw Zone - July 22
You want to understand the status quo, align a data lake zoning strategy and lay a foundation for data governance with an enterprise data catalog. You will also leverage this foundation to help identify strategies to ingest data into your data lake, whilst preserving lineage.
Part 2: Structured Zone - July 29
You are interested in ETL and/or ELT strategies that suit the volumes and varieties of your enterprise and allow you to leverage rapidly evolving storage and compute technologies. We will also discuss governance considerations for your transformation layer.
Part 3: Curated Zone - August 5
You have transformed raw data, established a structured zone and you want curate data sets with quality metrics. We will discuss the importance of a well-defined data quality management strategy and how that will augment your governance.
Part 4: Consumer Zone - August 12
You have raw, structured and curated data sets with lineage all the way to the source. You have a diverse data consumer base, your goal is to democratize your data lake assets and do so within your governance purview.
Part 5: Analytics Zone - August 19
You almost reached your data management Nirvana; however, you have the need to enrich your datasets and create your own data pipelines. You need this data to be trusted, governed, and without time-to-insight delays.