Precisely

SEPTEMBER 6, 2023

.” Poor data quality impedes the success of data programs, hampers data integration efforts, limits data integrity causing big data governance challenges. To truly succeed in an increasingly data-driven world, organizations need data governance. The results are clear.

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Precisely

SEPTEMBER 8, 2023

According to a recent report on data integrity trends from Drexel University’s LeBow College of Business , 41% reported that data governance was a top priority for their data programs. Automating functions in support of data governance provides a range of important benefits.

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Precisely

MARCH 13, 2023

Despite that understanding, many organizations lack a clear framework for organizing, managing, and governing their valuable data assets. In many cases, that realization prompts executive leaders to create a data governance program within their company. In many organizations, that simply isn’t the case.

Data Governance 52

Data Governance Government Generalist Data 52

Cloudera

NOVEMBER 2, 2021

More use cases must be deployed to drive more insight and value; more data needs to be made available to more users. Data governance: three steps to success. It is safe to assume that businesses understand the importance of good data governance. Know what data you have. Better governance for better outcomes.

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Knowledge Hut

APRIL 20, 2023

Data governance refers to the set of policies, procedures, mix of people and standards that organisations put in place to manage their data assets. It involves establishing a framework for data management that ensures data quality, privacy, security, and compliance with regulatory requirements.

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Data Engineering Podcast

MAY 20, 2021

Summary Data governance is a phrase that means many different things to many different people. This is because it is actually a concept that encompasses the entire lifecycle of data, across all of the people in an organization who interact with it. data stewards, business glossaries, etc.)

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AltexSoft

MARCH 2, 2023

As the amount of enterprise data continues to surge, businesses are increasingly recognizing the importance of data governance — the framework for managing an organization’s data assets for accuracy, consistency, security, and effective use. Projections show that the data governance market will expand from $1.81

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Data Governance Government Healthcare Programming 52

Cloudera

MARCH 9, 2021

In this blog, we’ll highlight the key CDP aspects that provide data governance and lineage and show how they can be extended to incorporate metadata for non-CDP systems from across the enterprise. can be derived from a supertype definition. can be derived from a supertype definition. Processes: File transfer process.

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Data Governance Government Metadata Datasets 95

Monte Carlo

JULY 11, 2023

Even if data is accurate within individual records, inconsistencies or discrepancies across different sources or datasets can reduce its overall quality. Inconsistencies may arise due to variations in data formats, coding schemes, or definitions used by different systems or data providers.

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Data Cleanse Datasets Data Governance Government 40

Monte Carlo

JULY 10, 2023

The same is true with data. If all the information in a data set is accurate and precise, but key values or tables are missing, your analysis won’t be effective. That’s where the definition of data completeness comes in.

Data Collection 40

Data Collection Data Governance Government Data 40

Snowflake

MARCH 19, 2024

We saw that collectively, organizations are definitely preparing their data to be used more effectively with powerful, new AI technologies. The most marked finding was around governance. Strong data governance is essential to meet security and compliance obligations, but it is often regarded as a hindrance.

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Data Governance Government Unstructured Data Programming Language 117

Snowflake

MAY 22, 2024

Snowflake has entered into a definitive agreement to acquire the TruEra AI observability platform, which provides leading capabilities to evaluate and monitor LLM apps and ML models in production. TruEra’s capabilities complement the AI and ML data governance functionalities we already provide in the AI Data Cloud.

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Monte Carlo

AUGUST 30, 2023

Your test passes when there are no rows returned, which indicates your data meets your defined conditions. Also, remember data governance. Stored test failure data should adhere to your relevant policies or regulations, including data privacy and security, and is only made accessible to the appropriate team members.

SQL 52

SQL Datasets Database High Quality Data 52

Zalando Engineering

JULY 28, 2021

Its form needs to be defined in a logical data model. This is a set of definitions of tables and columns in which the consolidated record pulled, matched, and merged from the different sources is stored. The logical data model is not the only deliverable in such an MDM project.

Technology 52

Technology Data Systems Data Governance 52

Data Engineering Podcast

FEBRUARY 18, 2024

Your host is Tobias Macey and today I'm interviewing Dain Sundstrom about building a data lakehouse with Trino and Iceberg Interview Introduction How did you get involved in the area of data management? To start, can you share your definition of what constitutes a "Data Lakehouse"?

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Monte Carlo

AUGUST 25, 2023

The inception of the data lakehouse came about as cloud warehouse providers began adding features ordinarily associated with lakes, as seen in platforms like Redshift Spectrum and Delta Lake. Conversely, data lakes began incorporating warehouse-like features, such as including SQL functionality and schema definitions.

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Data Engineering Podcast

MARCH 10, 2024

Links Project Nessie Article: What is Nessie, Catalog Versioning and Git-for-Data? Starburst does all of this on an open architecture with first-class support for Apache Iceberg, Delta Lake and Hudi, so you always maintain ownership of your data. Links Project Nessie Article: What is Nessie, Catalog Versioning and Git-for-Data?

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Knowledge Hut

MARCH 7, 2024

Two, it creates a commonality of data definitions, concepts, metadata and the like. The traditional data management and data warehouses, and the sequence of data transformation, extraction and migration- all arise a situation in which there are risks for data to become unsynchronized.

Big Data 98

Big Data Bytes Data Governance Raw Data 98

ThoughtSpot

SEPTEMBER 13, 2023

Speed to insight : Empower analysts with more flexibility and speed when data modeling , delivering searchable data into the hands of business users quicker than ever before. Self service: Ensure there is a single, trusted definition of your data models across the business.

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BI Google Cloud Data Governance Business Intelligence 80

François Nguyen

JANUARY 18, 2021

To finish the trilogy (Dataops, MLops), let’s talk about DataGovOps or how you can support your Data Governance initiative. Last part, it was added the data security and privacy part. Every data governance policy about this topic must be read by a code to act in your data platform (access management, masking, etc.)

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Cloudera

MARCH 27, 2023

Our wizard is Data Governance Director Suvayu Bose (no relation) who employs a very practical approach to data governance: establish C-suite commitment to the program, set strategic goals, identify data owners and data stewards, then get right to negotiating data definitions cross-functionally.

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Data Engineering Podcast

MARCH 3, 2024

What are some of the useful clarifying/scoping questions to address when deciding the path to deployment for different definitions of "AI"? Organizations can easily fall into the trap of green-lighting an AI project before they have done the work of ensuring they have the necessary data and the ability to process it.

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Programming Data Lake High Quality Data Data Pipeline 162

Data Engineering Weekly

MARCH 17, 2024

The author explores the evolving landscape of data product standards, highlighting the necessity for unified standards to ensure interoperability and manage the data economy effectively. It discusses the significance of data governance, sharing history, and generative AI's impact on data economy standards.

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Data Engineering Data Engineer Engineering Data Governance 70

Monte Carlo

MAY 20, 2024

It is primarily concerned with the accuracy and proper usage of data at a micro level. Data Type : Information on whether the element is an integer, string, date, etc. Description : A clear definition of what the data element represents. Allowed Values : A list of acceptable inputs for the data element.

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Monte Carlo

MAY 14, 2024

The new kids on the table format block Within the last five or six years, as data management needs have grown in complexity and scale, newer table formats have emerged. These live tables streamline the management of complex data transformations, incorporating error handling and performance optimization directly into data pipeline definitions.

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Databand.ai

AUGUST 30, 2023

Measuring data integrity is more complex, as it involves assessing the consistency, reliability, and trustworthiness of data throughout its lifecycle. Methods While data accuracy and data integrity have similar objectives, the methods used to achieve them are different.

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Data Integration Data Cleanse Data Validation Data Governance 52

Snowflake

MARCH 21, 2023

In February, Snowflake launched new features around streaming data ingestion and data governance and improved SQL experience and performance, with enhancements to Search Optimization Service and more. Read on to learn about everything new announced in February.

Retail 72

Retail Healthcare Data Ingestion Consulting 72

Data Engineering Podcast

NOVEMBER 19, 2023

Trusted by the teams at Comcast and Doordash, Starburst delivers the adaptability and flexibility a lakehouse ecosystem promises, while providing a single point of access for your data and all your data governance allowing you to discover, transform, govern, and secure all in one place.

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Precisely

FEBRUARY 6, 2023

If digital transformation initiatives are to deliver on their promises, they need accurate, consistent, contextualized, and rich data. What Is Data Integrity? Until recently, the business community has lacked a clear and consistent definition of data integrity.

Data Integration 52

Data Integration Data Governance Government Raw Data 52

Cloudera

MARCH 14, 2023

They are being asked to deliver not just theoretical data strategies, but to roll up their sleeves and solve for the very real problems of disparate, heterogenous, and rapidly expanding data sources that make it a challenge to meet increasing business demand for data — and do it all while managing costs and ensuring security and data governance.

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Designing Data Pipeline Data Governance Government 78

François Nguyen

MARCH 7, 2021

The right problem is to solve is this one ; to have different teams working on different subjects (data domains) and still be able to share and cooperate together. ” I would have added data teams to metadata and data management. Now you have these data domains, you will need to personify it with a Data Domain Owne r.

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Government Data Governance Data Metadata 130

François Nguyen

MARCH 22, 2021

TL;DR After setting up and organizing the teams, we are describing 4 topics to make data mesh a reality. How do we build data products ? How can we interoperate between the data domains ? This is really for us the definition of a self serve platform.

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Technology Architecture Google Cloud Metadata 130

Christophe Blefari

JUNE 16, 2023

The power of pre-commit and SQLFluff —SQL is a query programming language used to retrieve information from data storages, and like any other programming language, you need to enforce checks at all times. Cube announcements ; Data Graph and Orchestration API — This is 2 announcement from Cube.

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Programming Language SQL PostgreSQL Data 130

Monte Carlo

NOVEMBER 7, 2023

They aren’t just practitioners in the data field—they’re experts in their own rights—pioneering the future of data reliability, data quality, trustworthy AI, and data governance across industries.

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Insurance Finance Education Data Governance 59

Lyft Engineering

OCTOBER 3, 2023

Data quality is an amorphous term, with various definitions depending on the context. In Verity, we defined data quality as follows: Verity’s Definition of Data Quality The measure of how well data can be used as intended. Five aspects of data quality with the definition in italics and an example in quotes.

Big Data 84

Big Data Metadata Data Warehouse Data 84

Monte Carlo

SEPTEMBER 27, 2023

We’re also excited to announce Monte Carlo’s participation in the Alation Open Data Quality Initiative , a program designed to give Alation customers the freedom to choose the data quality or observability solution of their choice to expand data trust in the Alation platform.

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The Modern Data Company

FEBRUARY 2, 2023

Finally, in the drive to enable more self-service, your organization will achieve a lot of positive things: better understanding of the breadth of data available, more complete cataloging and definition of both data assets and business problems, and increased usage of analytics as your organization becomes more data-driven.

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