DataOps, a methodology used by data teams to improve the quality of data analytics, is a complex topic. Industry leaders such as LinkedIn, Airbnb, and Uber have created their own operations platforms. Without open standards currently in place, Cloudera promises to incorporate an open standard in its upcoming product feature.
What happens to an organization when they move from hundreds of reports to hundreds of models? They run into similar problems as before and need to make sure operational procedures are in place. Machine learning adds more complexity to production deployment compared to traditional business intelligence systems. Leading organizations have created their own internal proprietary systems to enable DataOps. However, they require significant effort and investment and lack consistency and standards. Also, not every organization can afford to invest heavily in this area due to a lack of maturity.
Cloudera launched a preview of its DataOps offering and intends to launch its open standard–supported product in 2020. Cloudera will let the open standard community define standards. Cloudera is also moving towards the Apache Atlas product and away from its proprietary Cloudera Navigator data governance tool.
Cloudera scores quite well in Info-Tech SoftwareReviews and continues to strengthen its market position:
Source: Cloudera at SoftwareReviews, January 2020
Adopting Apache Atlas and moving away from a proprietary tool such as Cloudera Navigator reaffirms Cloudera’s strategy to stay with the open-source ecosystem after merging with Hortonworks in 2019. Data science production deployment lacks standards, and they need to be established at the industry level. Apache Atlas provides a solid foundation to build upon DataOps repository and deployment standards. However, the industry currently lacks a comprehensive data science policy framework for model development, and that needs to be established to be successful with DataOps open standards.
Leverage our blueprint Break Down Data Silos With a Data-Centric Integration Strategy to guide your data integration.
IBM is changing the terms of its ubiquitous Passport Advantage agreement to remove entitled discounts on over 5,000 on-premises software products, resulting in an immediate price increase for IBM Software & Support (S&S) across its vast customer landscape.
The beauty of good story telling is its applicability to the most unexpected situations. In 1871, Lewis Carroll wrote about the evil Queen trying to convince Alice to work for her, with a promise of “jam to-morrow and jam yesterday – but never jam to-day.” Little did he know that this one statement would be used by economists, politicians, playwrights, and musicians long after he wrote it – it's time to add data analysts to the list.
PHEMI is a data privacy solution focused on keeping data-processing activities secure by redacting information based on the role of the accessor. Thus, allowing such data to be used for multiple use cases without compromising privacy.
Board International follows the trend of delivering solutions by opening a solution marketplace while strengthening customer trust by getting SOC-2 and SOC-3 certifications.
Boomi, a Dell Technologies business, has been known for its lack of hierarchy and relationship management capability in its Master Data Hub (MDH) offering. Acquiring Unifi Software does not seem to fill this void but could even cannibalize MDH – unless the two products are merged into one.
Orchestra Networks was earning attention even before TIBCO’s acquisition. Now that it is part of the TIBCO family of software products, it can become the centerpiece of a very powerful data management, governance, integration, and analytics platform.
The EU plans to invest €6 billion to build a single European data space, reports EURACTIV. The envisioned space will house personal, business, and “high-quality industrial data” and create the infrastructure for data sharing and use across businesses and nations.
Databricks, a data processing and analytics platform with a strong focus on AI and ML, has partnered with Immuta to deliver automated end-to-end data governance for AI, data science, and ML projects.
There’s a proliferation of AI-driven/AI-powered/AI-[insert-your-own-favorite-verb-here] tools and products on the market, because AI – and its underlying technology, machine learning – is sexy and it sells. (And, in some cases, delivers.) We decided to take a look at one of the vendors, AnswerRocket.