Alation

APRIL 25, 2023

That means if you haven’t already incorporated a plan for data governance into your long-term vision for your business, the time is now. Let’s take a closer look at what data governance is — and the top five mistakes to avoid when implementing it. 5 common data governance mistakes 1.

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Octopai

JULY 18, 2019

Add to that the fact that the service providers are typically scrutinized at a highly detailed level by government regulators—so much so that in some countries, the government is the sole service provider. Healthcare and Data Governance. All of the challenges described above, among others, are data problems.

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Metadata Management Data Governance Insurance 48

Alation

FEBRUARY 13, 2020

In an earlier blog, I defined a data catalog as “a collection of metadata, combined with data management and search tools, that helps analysts and other data users to find the data that they need, serves as an inventory of available data, and provides information to evaluate fitness data for intended uses.”.

Metadata 52

Metadata Management Data Lake Data Governance 52

Octopai

FEBRUARY 12, 2020

Like any good puzzle, metadata management comes with a lot of complex variables. That’s why you need to use data dictionary tools, which can help organize your metadata into an archive that can be navigated with ease and from which you can derive good information to power informed decision-making. Why Have a Data Dictionary? #1

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erwin

FEBRUARY 28, 2024

One of the key ingredients to ensure data is really embedded in an organization, and one of the key enablers to increase the strategic impact of data, is the setup of a successful data governance program. Technology is an enabler, and for data governance this is essentially having an excellent metadata management tool.

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Alation

SEPTEMBER 7, 2021

In the previous blog , we discussed how Alation provides a platform for data scientists and analysts to complete projects and analysis at speed. In this blog we will discuss how Alation helps minimize risk with active data governance. So why are organizations not able to scale governance? Meet Governance Requirements.

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erwin

JUNE 26, 2020

It’s no surprise that most organizations’ data is often fragmented and siloed across numerous sources (e.g., legacy systems, data warehouses, flat files stored on individual desktops and laptops, and modern, cloud-based repositories.). Three Types of Metadata in a Data Catalog. Technical Metadata.

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AWS Big Data

MARCH 7, 2023

Analytics reference architecture for gaming organizations In this section, we discuss how gaming organizations can use a data hub architecture to address the analytical needs of an enterprise, which requires the same data at multiple levels of granularity and different formats, and is standardized for faster consumption.

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Octopai

APRIL 24, 2023

This new native integration enhances our data lineage solution by providing seamless integration with one of the most powerful cloud-based data warehouses, benefiting data teams and enabling support for a broader range of data lineage, discovery, and catalog.

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erwin

JULY 2, 2020

This matters because, as he said, “By placing the data and the metadata into a model, which is what the tool does, you gain the abilities for linkages between different objects in the model, linkages that you cannot get on paper or with Visio or PowerPoint.” Data Modeling with erwin Data Modeler. George H., For Rick D.,

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erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. Creating a High-Quality Data Pipeline.

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Alation

DECEMBER 15, 2022

December 2012: Alation forms and goes to work creating the first enterprise data catalog. Later, in its inaugural report on data catalogs, Forrester Research recognizes that “Alation started the MLDC trend.”. May 2016: Alation named a Gartner Cool Vendor in their Data Integration and Data Quality, 2016 report.

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Metadata Data Governance Data Quality Marketing 52

Alation

AUGUST 30, 2022

We continue to make deep investments in governance, including new capabilities in the Stewardship Workbench, a core part of the Data Governance App. Centralization of metadata. A decade ago, metadata was everywhere. Consequently, useful metadata was unfindable and unusable. Then Alation came along.

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Metadata Data Quality Data Governance Machine Learning 52

IBM Big Data Hub

JUNE 8, 2022

However, a foundational step in evolving into a data-driven organization requires trusted, readily available, and easily accessible data for users within the organization; thus, an effective data governance program is key. Integrating data across this hybrid ecosystem can be time consuming and expensive.

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IBM Big Data Hub

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. Improved trust and confidence in data.

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Metadata Data Quality Data-driven Data Governance 52

Alation

FEBRUARY 13, 2020

Data curation is important in today’s world of data sharing and self-service analytics, but I think it is a frequently misused term. When speaking and consulting, I often hear people refer to data in their data lakes and data warehouses as curated data, believing that it is curated because it is stored as shareable data.

Metadata 52

Metadata Data Warehouse Data Lake Data Governance 52

erwin

APRIL 27, 2022

Best Data Governance Solution (erwin Data Intelligence). Best Data Modeling Solution (erwin Data Modeler). Best Data Security Solution (Quest ApexSQL). In data warehousing, the data is extracted and transported from production database(s) into a data warehouse for reporting and analysis.

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AWS Big Data

MARCH 10, 2023

They enable transactions on top of data lakes and can simplify data storage, management, ingestion, and processing. These transactional data lakes combine features from both the data lake and the data warehouse. One important aspect to a successful data strategy for any organization is data governance.

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Andrew White

DECEMBER 9, 2019

The outline of the call went as follows: I was taking to a central state agency who was organizing a data governance initiative (in their words) across three other state agencies. All four agencies had reported an independent but identical experience with data governance in the past.

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Cloudera

NOVEMBER 12, 2020

At these times, they run business growth reports, shareholder reports, and financial reports for their earnings calls, to name a few examples. Cloud deployments for suitable workloads gives you the agility to keep pace with rapidly changing business and data needs. How Burst to Cloud can solve your data center pressure.

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AWS Big Data

SEPTEMBER 25, 2023

With Amazon Redshift , you can run a complex mix of workloads on your data warehouse, such as frequent data loads running alongside business-critical dashboard queries and complex transformation jobs. We also see more and more data science and machine learning (ML) workloads.

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Octopai

MAY 5, 2020

They collected insights from 293 business and IT professionals across a wide range of industries, shining light on why automation metadata operations and the business glossary are priorities for organizations today. Use Case #2: Daily Data Operations. Another BI challenge comes from everyday metadata management operations.

Metadata 52

Metadata Reporting Data Warehouse Management 52

IBM Big Data Hub

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. Perform data quality monitoring based on pre-configured rules.

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datapine

SEPTEMBER 29, 2022

In this article, we will detail everything which is at stake when we talk about DQM: why it is essential, how to measure data quality, the pillars of good quality management, and some data quality control techniques. But first, let’s define what data quality actually is. 2 – Data profiling. 4 – Data Reporting.

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Octopai

DECEMBER 10, 2019

Well, scoot over Templeton, because it’s also going to be the year of the Automated Business Glossary for business intelligence and data governance teams everywhere. In addition, proper business glossary software provides a pathway to build lineage and for metadata management for analysis of the data contained within it.

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Data Virtualization

OCTOBER 22, 2021

Since its first incarnation almost 35 years ago in my IBM Systems Journal article, the data warehouse (DW) has remained a key architectural pattern for decision-making support. By decision-making support, I mean everything from simple reporting and querying to AI-based.

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Data Virtualization

OCTOBER 21, 2021

Since its first incarnation almost 35 years ago in my IBM Systems Journal article, the data warehouse (DW) has remained a key architectural pattern for decision-making support. By decision-making support, I mean everything from simple reporting and querying to AI-based.

Data Warehouse 52

Data Warehouse Reporting IT Metadata 52

Jet Global

JULY 2, 2019

The sheer scale of data being captured by the modern enterprise has necessitated a monumental shift in how that data is stored. From the humble database through to data warehouses , data stores have grown both in scale and complexity to keep pace with the businesses they serve, and the data analysis now required to remain competitive.

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Alation

DECEMBER 21, 2022

Transactional systems and data warehouses can then use the golden records as the entity’s most current, trusted representation. Data Catalog and Master Data Management. Early on, analysts used data catalogs to find and understand data more quickly. The MDM tool should help with this.

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Cloudera

MAY 12, 2021

In light of a year of unprecedented disruptions, where data has never been so important, and to reflect on the rapidly advancing world of data-led digital transformation, we are excited to announce this year’s 7 categories: DATA LIFECYCLE CONNECTION. SECURITY AND GOVERNANCE LEADERSHIP. DATA FOR GOOD.

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erwin

FEBRUARY 19, 2021

Metadata management is key to wringing all the value possible from data assets. However, most organizations don’t use all the data at their disposal to reach deeper conclusions about how to drive revenue, achieve regulatory compliance or accomplish other strategic objectives. What Is Metadata? Harvest data.

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Cloudera

FEBRUARY 16, 2022

Weak model lineage can result in reduced model performance, a lack of confidence in model predictions and potentially violation of company, industry or legal regulations on how data is used. . Within the CML data service, model lineage is managed and tracked at a project level by the SDX. Figure 03: lineage.yaml.

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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.

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Alation

FEBRUARY 13, 2020

A typical data catalog implementation process begins by defining the business and technical case, proceeds through technology selection and installation, then moves on to data discovery and populating the metadata catalog. Figure 1 – Data Catalog Implementation. Will data stewards assume curation responsibilities?

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Domino Data Lab

APRIL 3, 2019

Paco Nathan ‘s latest column dives into data governance. This month’s article features updates from one of the early data conferences of the year, Strata Data Conference – which was held just last week in San Francisco. In particular, here’s my Strata SF talk “Overview of Data Governance” presented in article form.

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Ontotext

MARCH 8, 2023

Rich metadata and semantic modeling continue to drive the matching of 50K training materials to specific curricula, leading new, data-driven, audience-based marketing efforts that demonstrate how the recommender service is achieving increased engagement and performance from over 2.3 million users.

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Enterprise Knowledge Discovery Risk Data-driven 52

erwin

FEBRUARY 7, 2019

Organization’s cannot hope to make the most out of a data-driven strategy, without at least some degree of metadata-driven automation. The volume and variety of data has snowballed, and so has its velocity. As such, traditional – and mostly manual – processes associated with data management and data governance have broken down.

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