erwin

OCTOBER 31, 2019

The Regulatory Rationale for Integrating Data Management & Data Governance. Now, as Cybersecurity Awareness Month comes to a close – and ghosts and goblins roam the streets – we thought it a good time to resurrect some guidance on how data governance can make data security less scary.

Data Governance 105

Data Governance Metadata Risk Data Lake 105

AWS Big Data

APRIL 24, 2023

Building a data lake on Amazon Simple Storage Service (Amazon S3) provides numerous benefits for an organization. However, many use cases, like performing change data capture (CDC) from an upstream relational database to an Amazon S3-based data lake, require handling data at a record level.

Data Lake 77

Data Lake Data Governance Cost-Benefit Machine Learning 77

Jet Global

JULY 2, 2019

To address the flood of data and the needs of enterprise businesses to store, sort, and analyze that data, a new storage solution has evolved: the data lake. What’s in a Data Lake? Data warehouses do a great job of standardizing data from disparate sources for analysis. Taking a Dip.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

AWS Big Data

JANUARY 31, 2023

Data governance is the collection of policies, processes, and systems that organizations use to ensure the quality and appropriate handling of their data throughout its lifecycle for the purpose of generating business value.

Data Lake 79

Data Lake Data Governance Data Architecture Data Warehouse 79

CIO Business Intelligence

APRIL 1, 2024

Ensure that data is cleansed, consistent, and centrally stored, ideally in a data lake. Data preparation, including anonymizing, labeling, and normalizing data across sources, is key. You’ll also institute guardrails for data governance, data quality, data integrity, and data security.

Data Lake 121

Data Lake Consulting Uncertainty Risk 121

Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. Will the model correctly determine it is a muffin or get confused and think it is a chihuahua? The extent to which we can predict how the model will classify an image given a change input (e.g. Model Visibility.

Machine Learning 81

Machine Learning Modeling Metadata Recreation/Entertainment 81

CIO Business Intelligence

OCTOBER 13, 2023

Solutions data architect: These individuals design and implement data solutions for specific business needs, including data warehouses, data marts, and data lakes. Application data architect: The application data architect designs and implements data models for specific software applications.

Data Architecture 126

Data Architecture Data Warehouse Statistics Visualization 126

CIO Business Intelligence

FEBRUARY 16, 2023

Hence the drive to provide ML as a service to the Data & Tech team’s internal customers. All they would have to do is just build their model and run with it,” he says. That step, primarily undertaken by developers and data architects, established data governance and data integration. The offensive side?

Unstructured Data 102

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 102

AWS Big Data

MARCH 7, 2023

A data hub is a center of data exchange that constitutes a hub of data repositories and is supported by data engineering, data governance, security, and monitoring services. A data hub contains data at multiple levels of granularity and is often not integrated.

Analytics 69

Analytics Data Warehouse Data Lake Metadata 69

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. But the attempts to standardize data across the entire enterprise haven’t produced the desired results.

Data Governance 40

Data Governance Risk Metadata Management 40

Cloudera

JUNE 7, 2023

By now, almost everyone across the tech landscape has heard of the Zero Trust (ZT) security model, which assumes that every device, application, or user attempting to access a network is not to be trusted (see NIST definitions below). But as models go, the idea is easier than the execution.

Metadata 79

Metadata Data Lake Optimization Modeling 79

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. An expensive consulting engagement.

Analytics 66

Analytics Data Lake Data Governance Metadata 66

Ontotext

FEBRUARY 12, 2024

Determine ownership by making sure all teams involved in the data mesh own the quality of their domain data, ensure service-level agreements are met, and share that data with data contracts. Domain teams should continually monitor for data errors with data validation checks and incorporate data lineage to track usage.

Data Quality 69

Data Quality Data-driven Data Lake Data Governance 69

CIO Business Intelligence

AUGUST 2, 2023

With the first two layers, the business is the driver with IT in a support role, but with the data governance and architecture layer, IT and the business are side by side, working through complex decisions about governance and architecture together. What’s an example of a data problem that illustrates how the layers work?

Manufacturing 83

Manufacturing Data Architecture Strategy Data Strategy 83

IBM Big Data Hub

JANUARY 5, 2023

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

AWS Big Data

JANUARY 30, 2023

Many customers need an ACID transaction (atomic, consistent, isolated, durable) data lake that can log change data capture (CDC) from operational data sources. There is also demand for merging real-time data into batch data. Delta Lake framework provides these two capabilities.

Insurance 76

Insurance Data Lake Data-driven Management 76

CIO Business Intelligence

FEBRUARY 28, 2023

Giving businesses a head start in the AI space is the cloud-native database GaussDB, which offers high-performance, high-availability, and secure real-time data lake capability to maximise enterprises’ data value.

Digital Transformation 80

Digital Transformation Internet of Things Data Lake Enterprise 80

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. After all, Alex may not be aware of all the data available to her.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Ontotext

NOVEMBER 16, 2023

Data mesh solves this by promoting data autonomy, allowing users to make decisions about domains without a centralized gatekeeper. It also improves development velocity with better data governance and access with improved data quality aligned with business needs.

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

Cloudera

FEBRUARY 19, 2018

But when companies are looking towards new technologies such as data lakes, machine learning or predictive analytics, SAP alone is just not enough. To keep up with tech trends, businesses have to face the challenges of integrating SAP with non-SAP technologies and embark on a crusade against data silos. Governance.

Data Lake 46

Data Lake Finance Data Governance Big Data 46

IBM Big Data Hub

JULY 5, 2022

Data security & governance . Take control of your data governance, security and compliance with Db2’s comprehensive, built-in auditing, access control, and data visibility capabilities. Vektis improves healthcare quality through data . To learn more, visit IBM Db2 and our IBM data management page. .

Data Lake 96

Data Lake Data Warehouse Publishing Structured Data 96

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.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Cloudera

MAY 12, 2021

We welcome organizations that have built and deployed use cases for enterprise-scale machine learning and have industrialized AI to automate, secure, and optimize data-driven decision-making and/or applications to enter this category. HYBRID & MULTI-CLOUD INNOVATION. PEOPLE FIRST. A new award category for 2021.

Digital Transformation 66

Digital Transformation Machine Learning Optimization Data Lake 66

Birst BI

JANUARY 23, 2018

Data governance is a broad topic that people seem to agree is important, but still argue about the details. Data semantics are everything. Many IT and data management professionals posit that a single central data repository, such as a large cloud data warehouse or a data lake, is the definitive “single version of the truth.”

Data Warehouse 50

Data Warehouse Data Governance Data Lake Enterprise 50

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale.

Data Lake 113

Data Lake Metadata Optimization Statistics 113

Andrew White

OCTOBER 24, 2019

Here is my update analysis on my 1-1’s and interactions so far: Topic: Data Governance 24. Vision/Data Driven/Outcomes 28. Modern) Master Data Management 16. Data lake 4. Data Literacy 4. He is not in booth 2!!! AI/Innovation 3. AI/Automation 6. Rolls and Skills 5. Getting Started 6.

Recreation/Entertainment 49

Recreation/Entertainment Data Lake IT Insurance 49

IBM Big Data Hub

APRIL 25, 2023

Relational databases were adapted to accommodate the demands of new workloads, such as the data engineering tasks associated with structured and semi-structured data, and for building machine learning models. Semi-structured data needs to be reformatted and transformed to be loaded into tables.

Optimization 57

Optimization Strategy Data Warehouse Cost-Benefit 57

Alation

FEBRUARY 13, 2020

Modern data catalogs—originated to help data analysts find and evaluate data—continue to meet the needs of analysts, but they have expanded their reach. They are now central to data stewardship, data curation, and data governance—all metadata dependent activities. But data catalogs do much more.

Metadata 52

Metadata Management Data Lake Data Governance 52

AWS Big Data

JULY 21, 2023

Data-driven organizations treat data as an asset and use it across different lines of business (LOBs) to drive timely insights and better business decisions. This leads to having data across many instances of data warehouses and data lakes using a modern data architecture in separate AWS accounts.

Data Lake 84

Data Lake Data Warehouse Marketing Management 84

Alation

FEBRUARY 13, 2020

Expansion in our business model is driven by the number of users of the data catalog, which means that our average customer is virally successful relative to their initial investment. The Alation Data Catalog is taking years of data lake and self-service analytics investments and driving them from investments to insights.

Enterprise 52

Enterprise Data Lake Machine Learning Data-driven 52

Ontotext

MARCH 8, 2023

With the size of data and dropping attention spans of online users, digital personalization has become one of the top priorities for companies’ business models. As such, most large financial organizations have moved their data to a data lake or a data warehouse to understand and manage financial risk in one place.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Cloudera

AUGUST 4, 2021

And if data security tops IT concerns, data governance should be their second priority. Not only is it critical to protect data, but data governance is also the foundation for data-driven businesses and maximizing value from data analytics. But it’s still not easy. But it’s still not easy.

Data Governance 83

Data Governance Metadata Data-driven Enterprise 83

Alation

APRIL 6, 2023

Data governance is traditionally applied to structured data assets that are most often found in databases and information systems. A “Value at Risk” (VaR) model operated on a series of spreadsheets, which were built manually, via copy and paste.

Data Governance 52

Data Governance Metadata Cost-Benefit Structured Data 52

AWS Big Data

JULY 19, 2023

You can structure your data, measure business processes, and get valuable insights quickly can be done by using a dimensional model. Amazon Redshift provides built-in features to accelerate the process of modeling, orchestrating, and reporting from a dimensional model. Declare the grain of your data.

Modeling 67

Modeling Sales Data Warehouse Snapshot 67

Cloudera

NOVEMBER 10, 2021

Furthermore, Apache Ranger now supports Public Cloud objects stores like Amazon S3 and Azure Data Lake Store (ADLS). Inherited model in Sentry Vs Explicit model in Ranger. Ranger is a comprehensive solution that can enable, manage, and monitor data security across the entire CDP ecosystem.

Data Lake 74

Data Lake Management Metadata Modeling 74

AWS Big Data

MAY 7, 2024

Data governance is a key enabler for teams adopting a data-driven culture and operational model to drive innovation with data. Amazon DataZone allows you to simply and securely govern end-to-end data assets stored in your Amazon Redshift data warehouses or data lakes cataloged with the AWS Glue data catalog.

Metadata 74

Metadata Data Lake Data Processing Data-driven 74

DataKitchen

DECEMBER 7, 2021

In the book, author Zhamak Dehghani reveals that, despite the time, money, and effort poured into them, data warehouses and data lakes fail when applied at the scale and speed of today’s organizations. A distributed data mesh is a better choice. Disrupting Data Governance: A Call to Action, by Laura B.

Data-driven 246

Data-driven Data Governance Big Data Data Science 246