We recently had the pleasure to listen to two tech luminaries in the data management and analytics space. Darshan Joshi, SVP Technology at Informatica, sat down with Sudhir Hasbe, Director of Product Management for Google Cloud Platform for a quick “fireside chat” as part of our summit for enterprise architects. Given that we are in the midst of a global pandemic, this virtual dialogue discusses some of the trends affecting enterprise customers today. Darshan and Sudhir also talk about modernizing from on-premises data warehouses to cloud data warehouses and data lakes.
Moving to cloud data warehouses and data lakes
One of the major trends underway is seeded in the digital transformation that many enterprises are undergoing. This transformation has seen a vast majority of companies moving more and more of their data to the cloud. Historically, companies had been keeping their data in on-premises data warehouses. The problem though was the data was typically siloed, making it difficult to extract meaningful insights due to the difficulty in accessing the data and performing analysis across the data in various silos. Also, as the data warehouses got increasingly larger, they were also expensive. Some companies tried on-premises data lakes, but they proved hard to interoperate and still suffered from having siloed data.
Companies needed a “next-generation” platform so they could leverage the analytics to its fullest extent In addition, the basic needs of agility and flexibility were also important. Darshan recounted Informatica’s long history in helping companies with data migration and support for Google connectivity for Google Cloud Storage and Google BiqQuery. In fact, Informatica Intelligent Cloud Services (IICS), the industry-leading next-gen iPaaS, is now available on Google Cloud Platform (GCP).
To bolster speed and efficiency, Informatica brought compute to the data, rather than trying to move all the data. Google has begun doing the same as well. Sudhir discussed the recent launch of BigQuery Omni, a flexible, multi-cloud analytics solution that lets companies cost-effectively access and securely analyze data across Google Cloud, Amazon Web Services (AWS), and Azure (coming soon), without leaving the familiar BigQuery user interface (UI). No data has to move around now.
Customer successes with Google Cloud and Informatica
Darshan and Sudhir then recounted the success that Sunrun has had with using Informatica to help bring data to Google Cloud. Sunrun, a San Francisco-based solar company whose mission is to make solar simple, wanted to become more agile and flexible and allow their business to run in real-time by running its analytics and reports faster. By using Google Cloud with cloud application and data integration from IICS, Sunrun was able to use Google Cloud Storage and BigQuery as a cloud data lake and warehouse.
- Expanded base of analytics power users by 7x
- Enabled reporting and visualization development 3x faster
- Reduced infrastructure building time by 75%
And the future for data trends? Both talked about how artificial intelligence (AI) and machine learning (ML) would be instrumental in the digital transformation journeys that companies are embarking on. In order to AI and ML to truly work, it needs good data as a starting point. The Informatica data platform collects the metadata, adds metadata management and makes it available to CLAIRE, the AI engine for Informatica.