Migrating to a Data Lakehouse to Accelerate Business Value and Reduce Costs
Webinar Speaker: David Stodder, Senior Director of Research for BI, TDWI
Date: Thursday, March 30, 2023
Time: 12:00 p.m. PT / 3:00 p.m. ET
Cloud data migration is a top priority as organizations seek the advantages of cloud computing’s inherent scalability, elasticity, and flexibility, as well as the promise of lower costs. However, many organizations find themselves beset by disparate data and architecture challenges. They have multiple cloud data warehouses for structured data and separate data lakes for semi- and unstructured data, including real-time streams. Data scientists and data-savvy analysts cannot easily access all the data they need for predictive models and machine learning algorithms. Business users are dissatisfied with BI dashboards that are old and offer limited data visibility and exploration.
For many, just getting data from sources into cloud data lakes and data warehouses is a problem. It’s taking too long to load and transform data for multiple data platforms. Data pipelines are exploding in number, becoming a costly, time-consuming, resource-intensive headache. Organizations find that they are unable to govern sensitive data adequately. Ultimately, the chaos is causing businesses to miss opportunities. Data management and integration in the cloud is becoming more costly, not less.
Join this TDWI Webinar to learn how you can solve problems by establishing a data lakehouse as the centerpiece of a modern, cloud-based enterprise data stack. A data lakehouse enables you to bring together data warehouses and data lakes into one single unified platform for all your data, analytics, and AI use cases. By deploying modern tools for loading, transformation, and data pipeline orchestration, you can bring order to chaos and be far more productive in the cloud.
Topics to be covered include:
- TDWI research insights into today’s challenges and why moving to a modern enterprise data stack is critical
- How a cloud-native data lakehouse supports both data warehousing and AI/ML
- Best practices and modern solutions for streamlining data loading, transformation, and orchestration using code optional, GUI-based tooling
- Overcoming data governance challenges as data and workloads grow in volume and variety
- How you can achieve objectives for reducing data management and integration costs
Lead Partner Solutions Architect,
Soham Bhatt is a Solutions Architect leading the EDW and ETL modernization practice at Databricks. Before Databricks he worked at Toyota Motors on building their next generation Big Data Platform. Prior to that his background was in building Enterprise Data Warehouses for Fortune 100 companies with Inmon and Kimball methodologies. In his current role, he loves guiding his customers with best practices to modernize their EDWs to Databricks Lakehouse.
VP Product Marketing,
Mark Balkenende has had a long career of mastering and integrating data at a number of enterprise companies, including Motorola, Abbott Labs, and Walgreens. Mark is a developer at heart stuck in a Product Marketing role. He loves to geek out and explain how different technology and cloud stacks will help you evolve your business.