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

Rocket-Powered Data Science

MARCH 20, 2023

Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science. Datasphere is a data discovery tool with essential functionalities: recommendations, data marketplace, and business content (i.e.,

Data Warehouse 325

Data Warehouse Metadata Digital Transformation Unstructured Data 325

Smarten

AUGUST 4, 2023

If you want to optimize your analytical results, be sure that the augmented analytics solution you choose has seamless, self-serve data preparation capability. ‘As As you consider augmented analytics solutions, be sure to thoroughly review the features and functionality for data preparation.’

Data Lake 52

Data Lake Machine Learning Data Integration Optimization 52

Sisense

AUGUST 28, 2020

However, as a data team member, you know how important data integrity (and a whole host of other aspects of data management) is. In this article, we’ll dig into the core aspects of data integrity, what processes ensure it, and how to deal with data that doesn’t meet your standards.

Data Integration 101

Data Integration Testing Data Quality Data-driven 101

Sisense

OCTOBER 15, 2020

Every data professional knows that ensuring data quality is vital to producing usable query results. Streaming data can be extra challenging in this regard, as it tends to be “dirty,” with new fields that are added without warning and frequent mistakes in the data collection process.

Dashboards 98

Dashboards IoT Optimization Internet of Things 98

AWS Big Data

APRIL 19, 2023

Background The success of a data-driven organization recognizes data as a key enabler to increase and sustain innovation. The goal of a data product is to solve the long-standing issue of data silos and data quality. Mike is the author of two books and numerous articles. His Amazon author page

Technology 82

Technology Data-driven Machine Learning Sales 82

Data Virtualization

JULY 20, 2023

But there’s a lot of confusion in the marketplace today between different types of architectures, specifically data mesh and data fabric, so I’ll. The post Logical Data Management and Data Mesh appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Management 40

Management Data Integration IT Data Quality 40