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1. Modern Data Platform What does your organizations data platform look like? Most of you have a data warehouse with the following characteristics. Many of you may also have data lakes with data across multiple subject areas. It contains data of mixed value or perhaps potentially unknown value. Great platform for experimentation, quickly integrating new sources. Simply load files into an object storage, no schema, schema on read and then start analyzing it immediately. Not necessary, your data is scattered between these two independent platforms. Data Warehouse, A great platform for fast query performance with large number of concurrent users. And Data Lake which is great for data scientists and have acceptable performance. Are these two areas stove piped in your organization? • Platforms are owned by different teams • Address specific and limited problem statements, in Silos • Require major Integration efforts for holistic solution

2. Silos? Integrating Fragmented Databases Challenges • Development & Management • Data Consistency & Security • Availability & Scalability • Cross Site Consistency Data Warehouse • Curated, trusted data • High concurrency • Schema on write • Subject area • High Performance Data Lake • Data of mixed value • Lower concurrency • Schema on read • Multiple subject areas • Acceptable Performance Integration work will account for 50% of the time & cost of building a digital platform

3. Silos? Integrating Fragmented Databases Challenges • Development & Management • Data Consistency & Security • Availability & Scalability • Cross Site Consistency Data Warehouse • Curated, trusted data • High concurrency • Schema on write • Subject area • High Performance Data Lake • Data of mixed value • Lower concurrency • Schema on read • Multiple subject areas • Acceptable Performance Integration work will account for 50% of the time & cost of building a digital platform

4. Silos? Integrating Fragmented Databases Challenges • Development & Management • Data Consistency & Security • Availability & Scalability • Cross Site Consistency Data Warehouse • Curated, trusted data • High concurrency • Schema on write • Subject area • High Performance Data Lake • Data of mixed value • Lower concurrency • Schema on read • Multiple subject areas • Acceptable Performance Integration work will account for 50% of the time & cost of building a digital platform