CIO Business Intelligence

MARCH 24, 2023

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time. The program must introduce and support standardization of enterprise data.

Data Governance 142

Data Governance Management Metadata Data Quality 142

Ontotext

JANUARY 10, 2024

Limiting growth by (data integration) complexity Most operational IT systems in an enterprise have been developed to serve a single business function and they use the simplest possible model for this. In both cases, semantic metadata is the glue that turns knowledge graphs into hubs of data, metadata, and content.

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72

Rocket-Powered Data Science

FEBRUARY 15, 2023

Know thy data: understand what it is (formats, types, sampling, who, what, when, where, why), encourage the use of data across the enterprise, and enrich your datasets with searchable (semantic and content-based) metadata (labels, annotations, tags). The latter is essential for Generative AI implementations.

Strategy 289

Strategy Experimentation Uncertainty Machine Learning 289

CIO Business Intelligence

NOVEMBER 22, 2022

As a result, a growing number of IT leaders are looking for data strategies that will allow them to manage the massive amounts of disparate data located in silos without introducing new risk and compliance challenges. The fabric, especially at the active metadata level, is important, Saibene notes.

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

Alation

FEBRUARY 3, 2022

In order for data governance to continuously improve , practitioners need to think of data governance as a cyclical process. This process embeds continuous improvement into the system through steps that monitor and measure performance to (1) glean insights and (2) integrate those lessons into the governance system.

Data Governance 98

Data Governance Measurement Metadata Testing 98

Ontotext

FEBRUARY 7, 2024

So, on one hand, we can see our schema as a vocabulary that has different names and different standards, and, on the other, we can see it as a metadata object. In this way, the elements of the schema form a data dictionary or metadata dictionary, which we can then put in a metadata registry.

Metadata 52

Metadata Data Integration Measurement Data-driven 52

AWS Big Data

MARCH 7, 2023

It covers how to use a conceptual, logical architecture for some of the most popular gaming industry use cases like event analysis, in-game purchase recommendations, measuring player satisfaction, telemetry data analysis, and more. Unlike ingestion processes, data can be transformed as per business rules before loading.

Analytics 68

Analytics Data Warehouse Data Lake Metadata 68

Alation

FEBRUARY 7, 2023

The product collected an impressive amount of metadata, from the user interface to the database structure. It then translated all that metadata into an image resembling a spider’s web. That was my earliest taste of data lineage. I now realize that it was integration with a data catalog like Alation.

Metadata 52

Metadata Data Warehouse Visualization Data Quality 52

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data. Then, you transform this data into a concise format.

Data Strategy 66

Data Strategy Strategy Data Warehouse Prescriptive Analytics 66

Alation

MARCH 14, 2023

All critical data elements (CDEs) should be collated and inventoried with relevant metadata, then classified into relevant categories and curated as we further define below. Store Where individual departments have their own databases for metadata management, data will be siloed, meaning it can’t be shared and used business-wide.

Data Strategy 52

Data Strategy Strategy Metadata Data Quality 52

O'Reilly on Data

JULY 28, 2020

These measures are commonly referred to as guardrail metrics , and they ensure that the product analytics aren’t giving decision-makers the wrong signal about what’s actually important to the business. When a measure becomes a target, it ceases to be a good measure ( Goodhart’s Law ). Data Wrangling and Feature Engineering.

Marketing 362

Marketing Experimentation Metrics Testing 362

Alation

OCTOBER 5, 2021

What is data governance and how do you measure success? Data governance is a system for answering core questions about data. It begins with establishing key parameters: What is data, who can use it, how can they use it, and why? Why is your data governance strategy failing? Data governance and AI.

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

IBM Big Data Hub

APRIL 10, 2023

That is, it should support both sound data governance —such as allowing access only by authorized processes and stakeholders—and provide oversight into the use and trustworthiness of AI through transparency and explainability.

Strategy 92

Strategy Data Architecture Cost-Benefit Reporting 92

erwin

APRIL 16, 2021

Led by Frank Pörschmann of iDIGMA GmbH, an IT industry veteran and data governance strategist, this latest webinar focused on “ Data Governance Maturity & Tracking Progress.”. Data Governance Is Business Transformation. Data governance is about how an organization uses its data. erwin Data Intelligence.

Data Governance 128

Data Governance Metadata Cost-Benefit Digital Transformation 128

BI-Survey

FEBRUARY 23, 2023

Data knowledge is essential to data and analytics There is a clear understanding that data is an asset to the organization. Almost three quarters of respondents also state that they have recognized the need to invest in ways to access, link and understand metadata. These include tools for metadata management (e.g.,

Metadata 52

Metadata Data-driven Data Strategy Strategy 52

IBM Big Data Hub

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. Data quality Data quality is essentially the measure of data integrity.

Data Quality 66

Data Quality Data Integration Metadata Cost-Benefit 66

Alation

MARCH 22, 2022

As the latest iteration in this pursuit of high-quality data sharing, DataOps combines a range of disciplines. It synthesizes all we’ve learned about agile, data quality , and ETL/ELT. This produces end-to-end lineage so business and technology users alike can understand the state of a data lake and/or lake house.

Metadata 52

Metadata Cost-Benefit Data Quality Data Lake 52

Ontotext

JULY 6, 2023

This shift of both a technical and an outcome mindset allows them to establish a centralized metadata hub for their data assets and effortlessly access information from diverse systems that previously had limited interaction. There are four groups of data that are naturally siloed: Structured data (e.g.,

Cost-Benefit 52

Cost-Benefit Metadata Experimentation Risk 52

Ontotext

MAY 22, 2023

Master data management (MDM), on the other hand, is focused on ensuring data quality and consistency across different systems and applications. MDM creates a single, verified source of data that can be used throughout an organization, and enforce policies and standards to maintain data quality.

Management 59

Management Unstructured Data Metadata Cost-Benefit 59

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. So questions linger about whether transformed data can be trusted. Data Quality Obstacles.

Data Governance 40

Data Governance Risk Metadata Management 40

CDW Research Hub

MAY 29, 2019

Identify where your company currently stands in data governance, while keeping in mind your master data management plan, data quality goals, data stewardship, data lineage, and metadata. Start to develop a data governance framework. Take a data inventory and outline the data ecosystem.

Data Governance 40

Data Governance Data Quality ROI Metadata 40

Alation

MARCH 11, 2022

A data catalog with a Behavioral Analysis Engine will measure human behavior around data to locate your most valuable and actionable data. This data about data, AKA metadata , is an essential layer of your new meshy fabric. Again, a data catalog can automate the tedium of compliance at scale.

Metadata 52

Metadata Data Governance ROI Data Quality 52

AWS Big Data

FEBRUARY 13, 2023

A set of queries from the production cluster – This set can be reconstructed from the Amazon Redshift logs ( STL_QUERYTEXT ) and enriched by metadata ( STL_QUERY ). With this in mind, we tested the following cluster configurations and used the replay tool to take measurements of the performance of each cluster.

Snapshot 64

Snapshot Data Warehouse Testing Analytics 64

O'Reilly on Data

MARCH 31, 2020

You might have millions of short videos , with user ratings and limited metadata about the creators or content. Job postings have a much shorter relevant lifetime than movies, so content-based features and metadata about the company, skills, and education requirements will be more important in this case.

Management 332

Management Machine Learning Experimentation Metrics 332

erwin

APRIL 15, 2020

Rationalize external data dictionaries to our internal data dictionaries and understand where differences occur and how we will overcome those differences. Ingest to a quarantined area where it can be profiled and measured for quality, completeness, and correctness, and where necessary, cleansed.

Data Governance 134

Data Governance Metadata Testing Reporting 134

Alation

SEPTEMBER 7, 2021

In the next section, let’s take a deeper look into how these key attributes help data scientists and analysts make faster, more informed decisions, while supporting stewards in their quest to scale governance policies on the Data Cloud easily. Find Trusted Data. Verifying quality is time consuming.

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

BI-Survey

FEBRUARY 6, 2020

Although a common data model consisting of aligned structures and measures is needed for consistency and governance , it will not grant business departments the freedom required to efficiently analyze and interpret data. Data management has always been a challenge for companies.

Reporting 59

Reporting Optimization Enterprise Data Quality 59

Alation

JANUARY 26, 2023

Offer the right tools Data stewardship is greatly simplified when the right tools are on hand. So ask yourself, does your steward have the software to spot issues with data quality, for example? Do they have a system to manage the metadata for given assets? The IBM mainframe system is a strong example.

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

AWS Big Data

AUGUST 14, 2023

When are data products deprecated, and who is accountable for the consequences to their consumers? How do we define “risk” and “value” in the context of data products, and how can we measure this? Whose responsibility is it to justify the existence of a given data product? Measurement and Reporting X X.

Management 75

Management Risk Measurement Optimization 75

Octopai

JULY 12, 2020

An enormous amount of time was being wasted performing manual searches, as the BI team needed to frequently comb through the enterprise data warehouse’s fields to determine how each was calculated or to find their sources. Automated Data Lineage & Discovery Provides Enterprise-Wide Benefits.

Data Warehouse 58

Data Warehouse Data Quality Metadata Risk Management 58

Andrew White

MARCH 22, 2019

to weave together the governance and management of master data, application data, and less-widely shared data, and just enough enterprise metadata management. Your Future Requires You to Define Your Real Master Data. Data and analytics (and maybe AI) are getting very tired terms. Where the CDO reports.

Analytics 68

Analytics Metadata Data Governance Management 68

BI-Survey

MARCH 4, 2022

Due to steadily growing interest in the topic, we conducted this survey to better understand the flavors of data culture within organizations, the hurdles they are facing, the initiatives that are underway and of course the wins that have already been achieved with these measures.

Data-driven 52

Data-driven Data Strategy Data Governance Strategy 52

DataKitchen

SEPTEMBER 21, 2023

These layers help teams delineate different stages of data processing, storage, and access, offering a structured approach to data management. In the context of Data in Place, validating data quality automatically with Business Domain Tests is imperative for ensuring the trustworthiness of your data assets.

Testing 176

Testing Data Quality Predictive Modeling Metrics 176

AWS Big Data

NOVEMBER 16, 2023

Chargeback metadata Amazon Redshift provides different pricing models to cater to different customer needs. Redshift Serverless measures data warehouse capacity in RPUs, which are resources used to handle workloads. Automatic WLM manages the resources required to run queries.

Enterprise 80

Enterprise Data Warehouse Snapshot Cost-Benefit 80

Anmut

NOVEMBER 3, 2020

This means they make considered data investment plans – prioritising data investments to get the best ROI from this unique asset. Data isn’t subject to the same forces as other assets. Unlike capital or oil, data is not limited to a single owner or user.

Management 52

Management ROI Metadata Data Quality 52

Andrew White

JANUARY 9, 2022

First, how we measure emissions and carbon footprint is about data design and policy. In other words, D&A plays a key role in the foundational measuring angle. Link to item 6 on slide 27 is broken, [link] , for Dashboard to measure business impact, can you provide a current link?

Analytics 64

Analytics Measurement Modeling Data-driven 64

Alation

NOVEMBER 4, 2021

The practitioner asked me to add something to a presentation for his organization: the value of data governance for things other than data compliance and data security. Now to be honest, I immediately jumped onto data quality. Data quality is a very typical use case for data governance.

Data Governance 94

Data Governance Metadata Data Quality Enterprise 94