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The DataOps Vendor Landscape, 2021

DataKitchen

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. OwlDQ — Predictive data quality.

Testing 300
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8 data strategy mistakes to avoid

CIO Business Intelligence

Building a successful data strategy at scale goes beyond collecting and analyzing data,” says Ryan Swann, chief data analytics officer at financial services firm Vanguard. Creating data silos Denying business users access to information because of data silos has been a problem for years.

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Top 10 Analytics And Business Intelligence Trends For 2020

datapine

Businesses of all sizes are no longer asking if they need increased access to business intelligence analytics but what is the best BI solution for their specific business. Companies are no longer wondering if data visualizations improve analyses but what is the best way to tell each data-story.

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What is a Data Pipeline?

Jet Global

A data pipeline is a series of processes that move raw data from one or more sources to one or more destinations, often transforming and processing the data along the way. Data pipelines support data science and business intelligence projects by providing data engineers with high-quality, consistent, and easily accessible data.

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AWS Glue streaming application to process Amazon MSK data using AWS Glue Schema Registry

AWS Big Data

Organizations across the world are increasingly relying on streaming data, and there is a growing need for real-time data analytics, considering the growing velocity and volume of data being collected. Therefore, it’s crucial to keep the schema definition in the Schema Registry and the Data Catalog table in sync.

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Are Data Governance Bottlenecks Holding You Back?

erwin

While acknowledging that data governance is about more than risk management and regulatory compliance may indicate that companies are more confident in their data, the data governance practice is nonetheless growing in complexity because of more: Data to handle, much of it unstructured. Sources, like IoT.

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3 Takeaways from Gartner’s 2018 Data and Analytics Summit

DataRobot Blog

With AI infused throughout, the industry is moving towards a place where data analytics is far less biased, and where citizen data scientists will have greater power and agility to accomplish more in less time. 2) Line of business is taking a more active role in data projects. Sallam | Cindi Howson | Carlie J.