DataKitchen

OCTOBER 2, 2023

Data Teams and Their Types of Data Journeys In the rapidly evolving landscape of data management and analytics, data teams face various challenges ranging from data ingestion to end-to-end observability. It explores why DataKitchen’s ‘Data Journeys’ capability can solve these challenges.

Data Quality 100

Data Quality Testing Uncertainty Data Enablement 100

Octopai

JUNE 19, 2023

For business users Data Catalogs offer a number of benefits such as better decision-making; data catalogs provide business users with quick and easy access to high-quality data. This availability of accurate and timely data enables business users to make informed decisions, improving overall business strategies.

Metadata 88

Metadata Data Governance Measurement Risk Management 88

BI-Survey

FEBRUARY 17, 2020

With the growing interconnectedness of people, companies and devices, we are now accumulating increasing amounts of data from a growing variety of channels. New data (or combinations of data) enable innovative use cases and assist in optimizing internal processes. This is where data governance comes in. .

Data Governance 89

Data Governance Data Warehouse Data Quality Data Strategy 89

Grooper

AUGUST 19, 2019

Choosing the best analytics and BI platform for solving business problems requires non-technical workers to “speak data.”. A baseline understanding of data enables the proper communication required to “be on the same page” with data scientists and engineers. Master data management. Data governance.

Analytics 54

Analytics Machine Learning Data Science Data-driven 54

Alation

NOVEMBER 11, 2021

As IT leaders oversee migration, it’s critical they do not overlook data governance. Data governance is essential because it ensures people can access useful, high-quality data. Let’s take a look at some of the key principles for governing your data in the cloud: What is Cloud Data Governance?

Data Governance 52

Data Governance Data Quality Metrics Metadata 52

erwin

JULY 17, 2019

EA and BP modeling squeeze risk out of the digital transformation process by helping organizations really understand their businesses as they are today. Once you’ve determined what part(s) of your business you’ll be innovating — the next step in a digital transformation strategy is using data to get there. Do it faster.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

Andrew White

JANUARY 11, 2021

But we also know not all data is equal, and not all data is equally valuable. Some data is more a risk than valuable. Additionally, the value of data may change, and our own personal judgement of the the same data and its value may differ. Governance. Would really like to explore this one in debate.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52