Remove Data Analytics Remove Data Integration Remove Data Warehouse Remove Publishing
article thumbnail

Week in the Life of an Analyst at Gartner US IT Symposium (virtual) 2021

Andrew White

Lakehouse (data warehouse and data lake working together) 8. Data Literacy, training, coordination, collaboration 8. Data Management Infrastructure/Data Fabric 5. Data Integration tactics 4. Figure 3: The Data and Analytics (infrastructure) Continuum. Specific Vendor Questions 5.

IT 52
article thumbnail

Three Takeaways from Gartner’s 2019 Magic Quadrant for Data Management Solutions for Analytics

Cloudera

The Magic Quadrant (MQ) is an established, widely-referenced series of research reports published by the analyst firm Gartner, Inc. The January 2019 “Magic Quadrant for Data Management Solutions for Analytics” provides valuable insights into the status, direction, and players in the DMSA market.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Augmented data management: Data fabric versus data mesh

IBM Big Data Hub

The data fabric architectural approach can simplify data access in an organization and facilitate self-service data consumption at scale. Read: The first capability of a data fabric is a semantic knowledge data catalog, but what are the other 5 core capabilities of a data fabric? 11 May 2021. .

article thumbnail

How Tricentis unlocks insights across the software development lifecycle at speed and scale using Amazon Redshift

AWS Big Data

It has been well published since the State of DevOps 2019 DORA Metrics were published that with DevOps, companies can deploy software 208 times more often and 106 times faster, recover from incidents 2,604 times faster, and release 7 times fewer defects. Finally, data integrity is of paramount importance.

article thumbnail

Biggest Trends in Data Visualization Taking Shape in 2022

Smart Data Collective

If we talk about Big Data, data visualization is crucial to more successfully drive high-level decision making. Big Data analytics has immense potential to help companies in decision making and position the company for a realistic future. There is little use for data analytics without the right visualization tool.

article thumbnail

Quickly Clean Your SAP Supply Chain Data of Pollution

Jet Global

It then creates insights into what is happening at an operational level right now and in the foreseeable future by enriching the data with pre-built supply chain and finance calculations, on a transaction level (execution status, order bottlenecks) and in the form of operational KPIs (delivery reliability, stock level). Clean data is here.

article thumbnail

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.