The Future of the Data Lakehouse
Wednesday, October 20, 2021 | Original broadcast
Open and flexible: analyze any database, any application, from anywhere
The data you need to run your business comes from many sources within and outside your organization and in a variety of formats: financial and manufacturing applications on-premises and in the cloud, online transactions from mobile devices, IoT sensors, line-of-business databases, and social media, to name a few. Some of this data is structured as transactions in relational databases, other data is unstructured as in social media posts or videos, and yet other data is somewhere in between. How do you link, correlate, and analyze these varied outputs and effectively use your data to turn insights into new products or services that increase revenues?
Greg Pavlik, senior vice president of Data and AI Services at Oracle, shares how customers are using Oracle Cloud Infrastructure (OCI) to build a lakehouse that provides an efficient platform for integrating all your data—whether in a data warehouse, data lake, or application output—and adds analytics capabilities and machine learning to help you get the most value out of your data.
Whether you’re a data warehouse builder looking to integrate new data sets, a systems integrator building next-generation analytics solutions, or an open-source developer using ML, Spark, and other cloud-native technologies—and regardless of where you are on your cloud journey—building a lakehouse on OCI can help you overcome the obstacles posed by too much data, too many formats, too many sources and make sense of it all.
Greg Pavlik, Senior Vice President, Data and AI Services, Oracle
Mervyn Lally, Senior Vice President and Chief Enterprise Architect, Experian Information Technology Services (EITS)
Bridget Long, PhD, Director, Business Intelligence and Analytics, Ingersoll Rand
Highlights: The Future of the Data Lakehouse (9:50)
Technical deep dive
Technical Demo: Autonomous Database Integration with the Data Lake (13:46)
Learn how to easily aggregate and discover all types of data to perform deeper analysis at scale. Understand how to get the most value from data warehouses and data lakes using SQL.
Technical Demo: Gaining Insights from Unstructured Content with OCI (14:15)
Get value from unstructured data using AI capabilities in OCI. See how you can use data integration, AI services, and Oracle Analytics Cloud to extract insights to implement a customer feedback analytics pipeline.
Global organizations improve performance and analytics by building a data lakehouse on OCI
Experian Accelerates Financial Inclusivity with a Data Lakehouse on OCI (1:59)
Experian improved performance by 40% and reduced costs by 60% when it moved critical data workloads from other clouds to a data lakehouse on OCI, speeding data processing and product innovation while expanding credit opportunities worldwide.
Ingersoll Rand Builds Foundation for Advanced Analytics with a Data Lakehouse on OCI (1:35)
Ingersoll Rand consolidated multiple, on-premises ERPs, data warehouses, and big data systems into a data lakehouse on OCI, giving the company a single source of truth for all data with better reliability and performance.
Seattle Sounders FC Apply Data for Line-Breaking Passes with Oracle Cloud (1:55)
Seattle Sounders FC built a lakehouse on OCI to manage 100x more data, generate 10x faster insights, and eliminated database management using Oracle Autonomous Data Warehouse and Analytics, OCI Data Science, Object Storage, and video management.
Accenture Uses a Data Lakehouse on OCI to Foster Innovation (1:53)
Using a data lakehouse built on OCI, Accenture integrates data from Oracle ERP, HCM, and CX applications with other data sources, helping clients get visibility and perform predictive analysis in areas such as diversity and inclusion.
OUTFRONT Media Evolves Digital Ads with Insights from Oracle Cloud (1:44)
OUTFRONT Media uses Oracle Cloud Infrastructure (OCI) for a data lakehouse to integrate and analyze mobile and social data, gaining fresh insights into how best to connect brands with audiences.
“By using Oracle Analytics and Autonomous Data Warehouse, our goal is to apply machine learning and spatial analysis to better track check cashing behavior that mitigates risk and prevents fraud in real time to help businesses and consumers more confidently engage in commerce.”
“Almost all sports now have huge datasets with unique characteristics. Investing in a secure, stable analytics and data science platform from Oracle Cloud Infrastructure will empower teams like ours to focus on what we’re good at: using our data to deliver more wins.”