DataKitchen

MAY 10, 2021

As organizations strive to become more data-driven, Forrester recommends 5 actions to take to move from one stage of insights-driven business maturity to another. . Intermediates: Build on your successes and work to scale your IDB capabilities across the enterprise using agile and adaptive DevOps, DataOps, and ModelOps processes. .

Data-driven 130

Data-driven Data Architecture Machine Learning Strategy 130

DataKitchen

OCTOBER 28, 2021

Machine learning (ML) models are computer programs that draw inferences from data — usually lots of data. One way to think of ML models is that they instantiate an algorithm (a decision-making procedure often involving math) in software and then, at relatively low cost, deploy it on a large scale. Addressing AI Bias With DataOps.

Testing 130

Testing IT Manufacturing Machine Learning 130

DataKitchen

JANUARY 17, 2022

To meet the demand for continuous, high-quality insight, the BA team implemented a DataOps “process hub.” A DataOps process hub instantiates all processes and workflows (i.e., A robust and vibrant process hub is a clear sign of data organizational maturity. . Figure 1: A DataOps Process Hub. The Solution. The Results.

Experimentation 130

Experimentation Data Lake Predictive Modeling Marketing 130

DataKitchen

OCTOBER 2, 2023

This fragmented ownership model complicates data updates and results in a constant influx of erroneous data, making it exceedingly difficult to maintain data quality. DataKitchen’s DataOps Observability can deliver these Data Journeys with little to no development and few, if any, changes to production processes.

Data Quality 100

Data Quality Testing Uncertainty Data Enablement 100

Ontotext

FEBRUARY 12, 2024

It requires a shift in mindset, changes in team structures, and maturity that doesn’t happen overnight. How data mesh is implemented varies depending on each organization’s maturity and capabilities. Then, identify potential domains and business units that are mature and ready to adopt this paradigm.

Data Quality 69

Data Quality Data-driven Data Lake Data Governance 69

Cloudera

NOVEMBER 27, 2023

2: The majority of Flink shops are in earlier phases of maturity We talked to numerous developer teams who had migrated workloads from legacy ETL tools, Kafka streams, Spark streaming, or other tools for the efficiency and speed of Flink. Vendors making claims of being faster than Flink should be viewed with suspicion. Takeaway No.

Advertising 84

Advertising Data Lake Data Warehouse ROI 84

DataRobot Blog

SEPTEMBER 13, 2022

They develop and continuously optimize AI/ML models , collaborating with stakeholders across the enterprise to inform decisions that drive strategic business value. What data scientists do is directly tied to an organization’s AI maturity level. Driving Innovation with AI: Getting Ahead with DataOps and MLOps.

Forecasting 52

Forecasting Data-driven Machine Learning Optimization 52

erwin

AUGUST 1, 2023

Intro erwin ® Data Modeler 12.5 Because of the ability to provide standardization and foundational stability through all these processes, data modeling is a crucial step to success, and erwin ® Data Modeler by Quest ® is celebrating its 30 th birthday by releasing its newest, most collaborative version to date. bring to you?

Modeling 52

Modeling Metadata Data Quality Data Governance 52

Alation

AUGUST 17, 2022

Maturity will increase over time through education and adoption.”. So, data culture and governance need a strong leader, charter, operating model, and budget (which is many times the hardest part). Focus on market and customer needs and define safe/compliant operating models. This is the baseline for data-driven organizations.

Data Governance 92

Data Governance Risk Data-driven Measurement 92

Alation

JANUARY 25, 2022

Automated Data Orchestration (AKA DataOps). DataOps is the leading process concept in data today. See Gartner’s “ How DataOps Amplifies Data and Analytics Business Value ”). Data fabric and DataOps are a part of the continued evolution of data management-centric approaches that improve data architecture, efficiency, and quality.

Metadata 52

Metadata IT Data-driven Metrics 52

Andrew White

JANUARY 11, 2021

But the specifics may change based in size, industry and maturity. Where does the Data Architect role fits in the Operational Model ? Assuming a data architect helps model and guide and assist D&A then they play a key role. Try a little DataOps or ModelOps and see if a small, skunks-like project fan turn some folks on.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

O'Reilly on Data

SEPTEMBER 11, 2019

2 in frequency in proposal topics; a related term, “models,” is No. An ML-related topic, “models,” was No. For example, even though ML and ML-related concepts —a related term, “ML models,” (No. But the database—or, more precisely, the data model —is no longer the sole or, arguably, the primary focus of data engineering.

IoT 26

IoT Big Data Data Warehouse Uncertainty 26