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

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 72

Analytics Data Warehouse Data Lake Metadata 72

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

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

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

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. Odds are, that which is most used by people.

Metadata 52

Metadata Data Governance ROI Data Quality 52

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

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

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. This solution provides the most flexibility.

Enterprise 86

Enterprise Data Warehouse Snapshot Cost-Benefit 86

Ontotext

MAY 22, 2023

At the heart of such tools is the extraction of fields from forms or specific attributes from documents. Luckily, the text analysis that Ontotext does is focused on tasks that require complex domain knowledge and linking of documents to reference data or master data. That’s something that LLMs cannot do.

Management 59

Management Unstructured Data Metadata Cost-Benefit 59

erwin

FEBRUARY 4, 2021

It uncovered a number of obstacles that organizations have to overcome to improve their data operations. 1 bottleneck, according to 62 percent of respondents, was documenting complete data lineage. Overcoming Data Governance Bottlenecks.

Data Governance 89

Data Governance Metadata Data Quality Risk Management 89

IBM Big Data Hub

JANUARY 9, 2024

Currently, no standardized process exists for overcoming data ingestion’s challenges, but the model’s accuracy depends on it. Increased variance: Variance measures consistency. Insufficient data can lead to varying answers over time, or misleading outliers, particularly impacting smaller data sets.

Enterprise 78

Enterprise Data Integration Data Quality Contextual Data 78

IBM Big Data Hub

OCTOBER 12, 2023

They’re built on machine learning algorithms that create outputs based on an organization’s data or other third-party big data sources. Among the tasks necessary for internal and external compliance is the ability to report on the metadata of an AI model.

Cost-Benefit 82

Cost-Benefit Metadata Data Governance Modeling 82

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

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. Is there a good map that shows the connections between data, advanced analytics, digital, innovation, etc. – Yes and no.

Analytics 64

Analytics Measurement Modeling Data-driven 64

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

Alation

DECEMBER 15, 2021

This includes: Assigning responsibility for implementing the policies and processes, Defining policies for sharing and processing data, Creating processes for naming and storing data, Establishing measurements for keeping data clean and usable. Choose a Metadata Storage Option. Productive reuse of metadata.

Data Governance 52

Data Governance Strategy Metadata Data Strategy 52

Alation

FEBRUARY 17, 2023

The firms that get data governance and management “right” bring people together and leverage a set of capabilities: (1) Agile; (2) Six sigma; (3) data science; and (4) project management tools. The overall program should set a 2-year vision, mission, and goals, and then focus on execution, measuring progress along the way.

Data Governance 52

Data Governance Data Quality Metadata Cost-Benefit 52

DataKitchen

JANUARY 23, 2023

DataOps Observability includes monitoring and testing the data pipeline, data quality, data testing, and alerting. Data testing is an essential aspect of DataOps Observability; it helps to ensure that data is accurate, complete, and consistent with its specifications, documentation, and end-user requirements.

Testing 130

Testing Data Governance Data Quality Data-driven 130

Alation

NOVEMBER 22, 2022

What Is Data Governance In The Public Sector? Effective data governance for the public sector enables entities to ensure data quality, enhance security, protect privacy, and meet compliance requirements. With so much focus on compliance, democratizing data for self-service analytics can present a challenge.

Data Governance 52

Data Governance Metadata Data-driven Unstructured Data 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?

Management 79

Management Risk Measurement Optimization 79

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. It is a great question.

Analytics 68

Analytics Metadata Data Governance Management 68