When: Thursday, March 16th, 2023 | 2 PM SGT/ 3 PM JPT
Today data engineering and artificial intelligence experts are often frustrated with the lack of high-quality, reliable and up-to-date data available for their work. Due to the known drawbacks of the two-tier data architecture & over populated data warehouse, 86% of analysts are forced to use out-of-date data which affects the accuracy of business intelligence.
Join us for a 60 minute webinar, where we will showcase how a Databricks Lakehouse architecture can help you keep overcome the challenges of traditional data warehouses and achieve performance benefits.
During the webinar we will talk about
- Problems a Data Lakehouse solves
- Reasons to choose a Data Lakehouse over other architecture options
- How the Databricks Lakehouse performs in comparison to other Data Structures & Cloud Data Warehouse
- Success Stories of customers benefitting from Databricks Lakehouse Implementation
- Q&A
Cannot Attend? Please register and get a copy of the recording post webinar.
Duration: 60 minutes (45 minute webinar + 15 minute Q&A)
Speakers
Cledwyn Menezes
Principal Consultant, Celebal Technologies
Cled is based in Singapore and is a business builder who focusses on using leading digital technologies to drive core business strategy, customer engagement and operations. Cled actively participates in various other areas including customer consulting, public speaking and mentoring/training those who want to know, learn, and implement the technology of tomorrow.
Gaurav Modi
Big Data Solution Architect, Celebal Technologies
Gaurav is a Data Solution Architect and an Azure expert with a wealth of experience in data migration and data analysis. He has a proven track record of success in data migration projects from legacy systems & on-premises environments to Azure Cloud and ensuring seamless big data transformation with innovative azure data solutions in the Manufacturing, Retail, and banking domains. He is highly skilled in end-to-end Solution architecture, development, deployment & debugging of complex data pipelines with a deep understanding of the latest advancements in data architecture.
