datapine

SEPTEMBER 29, 2022

1) What Is Data Quality Management? 4) Data Quality Best Practices. 5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data.

Data Quality 241

Data Quality Metrics Data-driven Management 241

Sisense

OCTOBER 15, 2020

Let’s look at a few ways that different industries take advantage of streaming data. How industries can benefit from streaming data. Automotive: Monitoring connected, autonomous cars in real time to optimize routes to avoid traffic and for diagnosis of mechanical issues. Optimizing object storage. Cleaning up dirty data.

Dashboards 98

Dashboards IoT Optimization Internet of Things 98

Ontotext

MARCH 27, 2024

For example, a node in an LPG with a given label does not guarantee anything about its properties and data type (because it is a string and represents no semantics). LPG lacks schema and semantics, which makes it inappropriate for publishing and sharing of data. This makes LPGs inflexible.

Modeling 69

Modeling Metadata Data Quality Enterprise 69

AWS Big Data

JULY 27, 2023

DataBrew is a visual data preparation tool that enables you to clean and normalize data without writing any code. The over 200 transformations it provides are now available to be used in an AWS Glue Studio visual job. Now that we identified the data quality issues to address, we need to decide how to deal with each case.

Visualization 83

Visualization Cost-Benefit Data Quality Interactive 83

AWS Big Data

MARCH 3, 2023

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.

Software 52

Software Data Lake Testing Cost-Benefit 52

Smart Data Collective

OCTOBER 13, 2021

There are countless examples of big data transforming many different industries. There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. Data virtualization is ideal in any situation where the is necessary: Information coming from diverse data sources.

Visualization 135

Visualization Cost-Benefit Big Data Prescriptive Analytics 135

DataKitchen

APRIL 26, 2021

At Workiva, they recognized that they are only as good as their data, so they centered their initial DataOps efforts around lowering errors. Hodges commented, “Our first focus was to up our game around data quality and lowering errors in production. GSK’s DataOps journey paralleled their data transformation journey.

Measurement 246

Measurement Metrics Data-driven Testing 246