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On March 9, Databricks rolled out its latest industry-specific lakehouse, this time for healthcare and life sciences. Healthcare and life sciences data have particular issues around data silos and a lack of format standardization, along with the usual complications around combining structured and unstructured data for analysis, making it difficult to analyze said data at scale. Migrating data to a data lake such as Databricks’ Lakehouse will enable more complex and nuanced analysis of medical data, allowing for better understanding of patients, hospital capacity, disease spread, and other medical concepts. Amalgam Insights’ Hyoun Park goes into further detail in TechTarget. Databricks Lakehouse for Healthcare and Life Sciences follows previous industry-specific lakehouse releases for Financial Services, and for Retail and Consumer Goods.
On March 9, Collibra, X, announced significant updates to its Data Intelligence Cloud. New capabilities include automatic validation rules in Collibra Data Quality and Observability to scale up enforcement of data quality and sensitive data discovery, new Data Quality workflows to prioritize data quality requests appropriately, automation of data curation for data stewards, and improved data visualization. In addition, considerable attention was given to integrations, with expanded support for Tableau and new support for Matillon, as well as a new browser extension providing context for data when viewing Tableau and PowerBI reports, among a number of other popular data sources.
Vyasa, a deep learning and analytics software provider, debuted Cortex, a data fabric management platform, this week. Cortex functions as a template builder for data fabrics by allowing users to build, manage, and provision access to data sources that are connected to Vyasa’s Layar data fabrics, thus creating new data fabric instances. Data fabrics keep disparate data silos connected within a given project, and Layar uses deep learning to tag and catalog the data to enable easy search capabilities; Cortex then provides a business-user-friendly interface to manage the projects.
On March 9, Atlan, a data collaboration platform, announced that it had closed a $50M Series B funding round. Insight Partners, Salesforce Ventures, and Sequoia Capital India co-led the round, with additional participation from Waterbridge Ventures and individual investors in the data space. The funding will go towards hiring throughout the company and expediting Atlan’s go-to-market strategy, as well as allowing for a potential ESOP buyback of up to $1.5M.
Xata, a user-friendly serverless database service for developers, announced earlier this week that it had raised a $30M Series A round of financing from Index Ventures and Redpoint Ventures. The funding will go towards product development. Xata also revealed that it had formed its board of directors, all women – an appropriate announcement for International Women’s Day on March 8. The board consists of CEO and Xata founder Monica Sarbu, Redpoint’s Erica Brescia as the director of the board, and Index’s Erin Price-Wright as a board observer.
On March 10, Oracle announced its Q3 2022 fiscal results. Revenues matched expectations, but earnings came in slightly below expectations. One potential contributing factor is that two of Oracle’s investments are underperforming – chip maker Ampere Computing had an operating loss, and gene sequencing company Oxford Nanopore has seen its stock price cut in half since the beginning of the year. These actually highlight two key trends. First, with the ongoing supply chain issues, large tech companies want to have more control over their ability to make and sell relevant hardware going forward, and recent geopolitical issues will exacerbate this trend further. Second, in addition to investing heavily enough in Oxford Nanopore that it affected their bottom line, Oracle also announced its intention to buy health record management software company Cerner for $28B. IBM may be getting out of healthcare, but Oracle seems eager to jump into the fray.
On March 10, Appen, a data annotation platform, and Mindtech, a computer vision-centric synthetic data creation platform, announced a commercial partnership between the two companies. Appen and Mindtech will provide both real and synthetic images, along with contextualized data and metadata annotation services, to encourage adoption of synthetic data in training AI models. As part of the investipartnership, Appen has also invested $3.7M to accelerate Mindtech’s growth.
On March 7, Anodot announced that it had joined the Snowflake Partner Network. Anodot provides anomaly detection and alerting, specializing in time series data. Joint customers of Anodot and Snowflake will be able to monitor this high-volume, high-frequency data collected in Snowflake for near-real-time insights.