article thumbnail

DataKitchen Resource Guide To Data Journeys & Data Observability & DataOps

DataKitchen

Webinar: Beyond Data Observability: Personalization DataKitchen DataOps Observability Problem Statement White Paper: ‘Taming Chaos’ Technical Product Overview Four-minute online demo Detailed Product: Documentation Webinar: Data Observability Demo Day DataKitchen DataOps TestGen Problem Statement White Paper: ‘Mystery Box Full Of Data Errors’ (..)

Testing 120
article thumbnail

The Human-Centric CDO: 3 Key Takeaways from the Gartner Data & Analytics Summit 2023 in London

Alation

D&A leaders from around the world gathered to discuss and find ways to overcome the latest challenges through strategies and innovations backed by data, analytics, and data science. The observations comprised a mix of classic (the power of people, data quality ), recent (architectures such as fabric and mesh ), and emerging (AI).

Insiders

Sign Up for our Newsletter

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

article thumbnail

BI Cubed: Data Lineage on OLAP Anyone?

Octopai

How much time has your BI team wasted on finding data and creating metadata management reports? In fact, BI projects used to take many months to complete and require huge numbers of IT professionals to extract data. However, over time new technologies and tools developed to ease data reporting and analysis.

OLAP 56
article thumbnail

A summary of Gartner’s recent DataOps-driven data engineering best practices article

DataKitchen

Too many teams have fragile, unmonitored production systems causing users to find problems with the data or reports. When these enablers are implemented, such as through DataKitchen products, teams will work faster, produce higher-quality results, and will be happier. Learn More Implement DataOps Data Engineering yourself.

article thumbnail

5 Signs You’re Using Bad Data to Make Business Decisions

Jet Global

It’s hard to answer that question because, truth be told, you don’t know you’re using bad data until it’s too late. . states that about 40 percent of enterprise data is either inaccurate, incomplete, or unavailable. Because bad data is the reason behind poor analytics. . Top 5 Warning Signs of Bad Data. Ted Friedman.

article thumbnail

A Data Analyst’s Guide to the Data Catalog

Alation

An enterprise data catalog is one such key asset. The Data Analyst Workflow. The workflow of a data analyst consists of four key stages: Discovery. When a businessperson poses a question to an analyst, the analyst starts by trying to find the right data. 7 Steps that Benefit from a Data Catalog. Preparation.

article thumbnail

Data Scalability Raises Considerable Risk Management Concerns

Smart Data Collective

Are you frustrated by an increase in the quantity of the data that your organization handles? Many businesses globally are dealing with big data which brings along a mix of benefits and challenges. A report by China’s International Data Corporation showed that global data would rise to 175 Zettabyte by 2025.