Alation

APRIL 18, 2023

On the contrary, data profiling today describes an automated process, where a data user can “point and click” to return key results on a given asset, like aggregate functions, top patterns, outliers, inferred data types, and more. In summary, data profiling is a critical component of a comprehensive data governance strategy.

IT 52

IT Metadata Data Quality Data Governance 52

IBM Big Data Hub

NOVEMBER 4, 2022

Data observability capability makes data quality checks upstream possible. Data Governance. Ensuring data quality is critical for data governance initiatives. IBM’s holistic approach to Data Quality.

Data Quality 57

Data Quality Metadata Data Governance Data-driven 57

erwin

APRIL 29, 2020

The CEO also makes decisions based on performance and growth statistics. An understanding of the data’s origins and history helps answer questions about the origin of data in a Key Performance Indicator (KPI) reports, including: How the report tables and columns are defined in the metadata? Who are the data owners?

Metadata 111

Metadata Data Governance Key Performance Indicator Data Quality 111

IBM Big Data Hub

JULY 6, 2022

To help companies avoid that pitfall, IBM has recently announced the acquisition of Databand.ai, a leading provider of data observability solutions. The data observability difference . starts at the data source, collecting data pipeline metadata across key solutions in the modern data stack like Airflow, dbt, Databricks and many more.

Metadata 57

Metadata Data Quality Snapshot Cost-Benefit 57

Alation

JUNE 2, 2022

In part one of this series, I discussed how data management challenges have evolved and how data governance and security have to play in such challenges, with an eye to cloud migration and drift over time. All Machine Learning uses “algorithms,” many of which are no different from those used by statisticians and data scientists.

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

Cloudera

AUGUST 10, 2021

SDX enhancements for improved platform and data governance, including the following notable features: . Atlas / Kafka integration provides metadata collection for Kafa producers/consumers so that consumers can manage, govern, and monitor Kafka metadata and metadata lineage in the Atlas UI. x, and 6.3.x,

Metadata 96

Metadata Sales Statistics Management 96

Octopai

JUNE 27, 2022

Work out your organization’s list of needs, sort them in order of priority, and use that as the basis for evaluating data catalog candidates. Manually updating the catalog every time a data asset changes is a Sisyphean task, and you’d require an army of Sisyphuses to even attempt it.

Management 72

Management Metadata Visualization Data Governance 72

TDAN

JANUARY 3, 2024

Edwards Deming, the father of statistical quality control, said: “If you can’t describe what you are doing as a process, you don’t know what you’re doing.” When looking at the world of IT and applied to the dichotomy of software and data, Deming’s quote applies to the software part of that pair.

Statistics 52

Statistics Software Data Quality IT 52

datapine

SEPTEMBER 29, 2022

This person (or group of individuals) ensures that the theory behind data quality is communicated to the development team. 2 – Data profiling. Data profiling is an essential process in the DQM lifecycle. Data monitoring and visualization: To be able to assess the quality of the data it is necessary to monitor it closely.

Data Quality 241

Data Quality Metrics Data-driven Management 241

Alation

MAY 24, 2022

generally available on May 24, Alation introduces the Open Data Quality Initiative for the modern data stack, giving customers the freedom to choose the data quality vendor that’s best for them with the added confidence that those tools will integrate seamlessly with Alation’s Data Catalog and Data Governance application.

Data Quality 98

Data Quality Data Governance Metadata Metrics 98

Alation

FEBRUARY 20, 2020

The head of sales needs the most up-to-date statistics on the state of the business, and they need it now — well, actually, yesterday. These recommendations organize the data about your data — what the industry for many years has called metadata. Creating a set of custom reports would take too much time.

Metadata 52

Metadata Analytics Dashboards Sales 52

Octopai

JANUARY 25, 2021

With such sensitive information at risk, the federal government passed the Health Insurance Portability and Accountability Act (HIPAA). This initiative is enforced to set standards for data governance in healthcare and keep medical information safe. million Americans.

Insurance 52

Insurance Metadata Statistics Reporting 52

O'Reilly on Data

FEBRUARY 11, 2020

They don’t have the resources they need to clean up data quality problems. The building blocks of data governance are often lacking within organizations. These include the basics, such as metadata creation and management, data provenance, data lineage, and other essentials. And that’s just the beginning.

Data Quality 304

Data Quality Metadata Data Governance Publishing 304

Cloudera

SEPTEMBER 15, 2022

As shown above, the data fabric provides the data services from the source data through to the delivery of data products, aligning well with the first and second elements of the modern data platform architecture. In June 2022, Barr Moses of Monte Carlo expanded on her initial article defining data observability.

Data Lake 79

Data Lake Data Architecture Data-driven Data Warehouse 79

IBM Big Data Hub

JULY 28, 2022

Metadata enrichment is about scaling the onboarding of new data into a governed data landscape by taking data and applying the appropriate business terms, data classes and quality assessments so it can be discovered, governed and utilized effectively. Scalability and elasticity.

Metadata 57

Metadata Data Quality Machine Learning Statistics 57

Domino Data Lab

JULY 22, 2019

data science’s emergence as an interdisciplinary field – from industry, not academia. why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

O'Reilly on Data

JULY 28, 2020

Acquiring data is often difficult, especially in regulated industries. Once relevant data has been obtained, understanding what is valuable and what is simply noise requires statistical and scientific rigor. Garbage in, garbage out” holds true for AI, so good AI PMs must concern themselves with data health.

Marketing 362

Marketing Experimentation Metrics Testing 362

Alation

JULY 7, 2022

In 2013 I joined American Family Insurance as a metadata analyst. I had always been fascinated by how people find, organize, and access information, so a metadata management role after school was a natural choice. The use cases for metadata are boundless, offering opportunities for innovation in every sector.

Metadata 52

Metadata Data-driven Insurance Statistics 52

O'Reilly on Data

MARCH 18, 2020

Whether it’s controlling for common risk factors—bias in model development, missing or poorly conditioned data, the tendency of models to degrade in production—or instantiating formal processes to promote data governance, adopters will have their work cut out for them as they work to establish reliable AI production lines.

Enterprise 311

Enterprise Deep Learning Data Governance Risk 311

AWS Big Data

JUNE 9, 2023

Data in customers’ data lakes is used to fulfil a multitude of use cases, from real-time fraud detection for financial services companies, inventory and real-time marketing campaigns for retailers, or flight and hotel room availability for the hospitality industry.

Data Lake 114

Data Lake Metadata Optimization Statistics 114

Cloudera

DECEMBER 20, 2021

Understanding that the future of banking is data-driven and cloud-based, Bank of the West embraced cloud computing and its benefits, like remote capabilities, integrated processes, and flexible systems. The platform is centralizing the data, data management & governance, and building custom controls for data ingestion into the system.

Metadata 86

Metadata Data-driven Cost-Benefit Digital Transformation 86

Domino Data Lab

AUGUST 8, 2019

In this episode I’ll cover themes from Sci Foo and important takeaways that data science teams should be tracking. First and foremost: there’s substantial overlap between what the scientific community is working toward for scholarly infrastructure and some of the current needs of data governance in industry. We did it again.”.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

IBM Big Data Hub

JANUARY 9, 2024

High variance in a model may indicate the model works with training data but be inadequate for real-world industry use cases. Limited data scope and non-representative answers: When data sources are restrictive, homogeneous or contain mistaken duplicates, statistical errors like sampling bias can skew all results.

Enterprise 81

Enterprise Data Integration Data Quality Contextual Data 81

Alation

JANUARY 25, 2022

As a reminder, here’s Gartner’s definition of data fabric: “A design concept that serves as an integrated layer (fabric) of data and connecting processes. In this blog, we will focus on the “integrated layer” part of this definition by examining each of the key layers of a comprehensive data fabric in more detail.

Metadata 52

Metadata IT Metrics Data-driven 52

Octopai

OCTOBER 6, 2019

– Visualizing your data landscape: By slicing and dicing the data landscape in different ways, what connections, relationships, and outliers can be found? – Analyzing the data: Using statistical methods, what insights can be gained by summarizing the data? What hidden trends can be identified?

Slice and Dice 57

Slice and Dice Metadata Visualization Data Governance 57

erwin

APRIL 21, 2020

Another foundational purpose of a data catalog is to streamline, organize and process the thousands, if not millions, of an organization’s data assets to help consumers/users search for specific datasets and understand metadata , ownership, data lineage and usage.

Measurement 97

Measurement Sales Data Governance Metadata 97

erwin

APRIL 21, 2020

Another foundational purpose of a data catalog is to streamline, organize and process the thousands, if not millions, of an organization’s data assets to help consumers/users search for specific datasets and understand metadata , ownership, data lineage and usage.

Measurement 96

Measurement Sales Data Governance Metadata 96

AWS Big Data

JANUARY 18, 2024

AWS Lake Formation and the AWS Glue Data Catalog form an integral part of a data governance solution for data lakes built on Amazon Simple Storage Service (Amazon S3) with multiple AWS analytics services integrating with them. DataZone automatically manages the permissions of your shared data in the DataZone projects.

Data Lake 91

Data Lake Metadata Data Governance Statistics 91

Andrew White

JANUARY 9, 2022

We found anecdotal data that suggested things such as a) CDO’s with a business, more than a technical, background tend to be more effective or successful, and b) CDOs most often came from a business background, and c) those that were successful had a good chance at becoming CEO or CEO or some other CXO (but not really CIO).

Analytics 64

Analytics Measurement Modeling Data-driven 64

O'Reilly on Data

MAY 21, 2019

You also need solutions that let you understand what data you have and who can access it. About a third of the respondents in the survey indicated they are interested in data governance systems and data catalogs. Metadata and artifacts needed for audits. Marquez (WeWork) and Databook (Uber). Source: O'Reilly.

Machine Learning 238

Machine Learning Technology Deep Learning Data Science 238

erwin

NOVEMBER 6, 2020

Prashant Parikh, erwin’s Senior Vice President of Software Engineering, talks about erwin’s vision to automate every aspect of the data governance journey to increase speed to insights. Although AI and ML are massive fields with tremendous value, erwin’s approach to data governance automation is much broader.

Data Governance 97

Data Governance Metadata Data-driven Visualization 97

Alation

SEPTEMBER 1, 2022

By definition, a data intelligence platform must serve a wide variety of user types and use cases – empowering them to collaborate in one shared space. The problem Data Intelligence Platforms solve. Why is a data intelligence platform needed in the first place? Get the new IDC Marketscape for Data Catalogs to learn more.

Reporting 52

Reporting Metadata Data Governance Interactive 52

DataKitchen

JANUARY 23, 2023

Data lineage can also be used for compliance, auditing, and data governance purposes. DataOps Observability Five on data lineage: Data lineage traces data’s origin, history, and movement through various processing, storage, and analysis stages. What is missing in data lineage?

Testing 130

Testing Data Governance Data Quality Data-driven 130

Andrew White

JANUARY 11, 2021

But we are seeing increasing data suggesting that broad and bland data literacy programs, for example statistics certifying all employees of a firm, do not actually lead to the desired change. New data suggests that pinpoint or targeted efforts are likely to be more effective. We do have good examples and bad examples.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52