DataKitchen

APRIL 13, 2021

We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . QuerySurge – Continuously detect data issues in your delivery pipelines. OwlDQ — Predictive data quality.

Testing 300

Testing Machine Learning Consulting Data Quality 300

TDAN

MAY 16, 2023

Data quality management (DQM) has advanced considerably over the years. The full extent of the problem was first recognized during the data warehouse movement in the 1980s.

Data Quality 52

Data Quality Data Warehouse Management Modeling 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.

Data Strategy 67

Data Strategy Strategy Data Warehouse Prescriptive Analytics 67

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.

Metadata 52

Metadata Data Governance Data Quality Technology 52

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

erwin

DECEMBER 12, 2019

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

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.

Analytics 70

Analytics Data Warehouse Data Lake Metadata 70

Timo Elliott

JANUARY 6, 2022

If storage costs are escalating in a particular area, you may have found a good source of dark data. If you’ve been properly managing your metadata as part of a broader data governance policy, you can use metadata management explorers to reveal silos of dark data in your landscape. Data sense-making.

IT 135

IT Metadata Data-driven Data Governance 135

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 104

Unstructured Data Data Lake Prescriptive Analytics Data Warehouse 104

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

FEBRUARY 12, 2024

This is especially beneficial when teams need to increase data product velocity with trust and data quality, reduce communication costs, and help data solutions align with business objectives. In most enterprises, data is needed and produced by many business units but owned and trusted by no one.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

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 73

Metadata Data Lake Data Processing Data-driven 73

AWS Big Data

JULY 13, 2023

To reflect the needs of their customers spread across different geographies and industries, Altron has organized their operating model across individual Operating Companies (OpCos). Data quality for account and customer data – Altron wanted to enable data quality and data governance best practices.

Optimization 89

Optimization B2B Data Quality Sales 89

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 80

Data Lake Data Governance Data Architecture Data Warehouse 80

erwin

AUGUST 7, 2019

A data catalog benefits organizations in a myriad of ways. With the right data catalog tool, organizations can automate enterprise metadata management – including data cataloging, data mapping, data quality and code generation for faster time to value and greater accuracy for data movement and/or deployment projects.

Metadata 90

Metadata Data Governance Data Quality Data Warehouse 90

erwin

DECEMBER 12, 2019

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

Alation

DECEMBER 21, 2022

Master Data Management (MDM) and data catalog growth are accelerating because organizations must integrate more systems, comply with privacy regulations, and address data quality concerns. What Is Master Data Management (MDM)? Data Catalog and Master Data Management. Assess Data Quality.

Management 52

Management Data Quality Metadata Testing 52

Laminar Security

DECEMBER 13, 2023

They offer a comprehensive solution to enhance your cloud security posture and effectively manage your data. The primary focus of discovery is to find all the places where data exists and identify the assets it resides in. Laminar leverages AI analysis in its foperations to enhance and automate the process of data discovery.

Data-driven 119

Data-driven Machine Learning Risk Deep Learning 119

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

Octopai

DECEMBER 12, 2021

How many different data systems do you have in your BI environment? The average data intelligence stack is comprised of the following components – ETL, data warehouse/database, analysis, and reporting – for each of which you may use one or multiple systems. Data catalogs. Metadata harvesting.

Metadata 98

Metadata Management Data Quality Data Governance 98

CIO Business Intelligence

JUNE 14, 2023

The certification focuses on the seven domains of the analytics process: business problem framing, analytics problem framing, data, methodology selection, model building, deployment, and lifecycle management. They know how to assess data quality and understand data security, including row-level security and data sensitivity.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

CDW Research Hub

SEPTEMBER 15, 2020

Creating a modern data platform that is designed to support your current and future needs is critical in a data-driven organization. Business leaders need to be able to quickly access data—and to trust the accuracy of that data—to make better decisions. Easy Access with a Secure Foundation.

Business Intelligence 52

Business Intelligence Prescriptive Analytics Unstructured Data Data Warehouse 52

Alation

JULY 28, 2022

It’s costly and time-consuming to manage on-premises data warehouses — and modern cloud data architectures can deliver business agility and innovation. However, CIOs declare that agility, innovation, security, adopting new capabilities, and time to value — never cost — are the top drivers for cloud data warehousing.

Data Warehouse 69

Data Warehouse Cost-Benefit Data Governance Data-driven 69

Cloudera

AUGUST 26, 2020

Talend’s data management environment running on Cloudera Data Platform enables you to create and execute Hadoop and Spark integration jobs, process and reconcile Big Data, and implement data governance processes using an intuitive drag-and-drop interface. Certified Data Quality Partner.

Machine Learning 83

Machine Learning Big Data Data Warehouse Data-driven 83

Ontotext

MARCH 18, 2020

Consequently, many data leaders today are striving to overcome these barriers by streamlining their enterprise knowledge management processes and practices. The knowledge graph model is one way of doing it and, not surprisingly, it has been in increasing demand in the last decade. Ontotext Knowledge Graph Platform.

Enterprise 59

Enterprise B2B Unstructured Data Machine Learning 59

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.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

Andrew White

DECEMBER 4, 2019

I argued that one vendors’ book on data quality was really about data governance; I argued that another vendors’ marketing message was totally upside down; and I argued that some approaches to achieving single source of truth were different from traditional approaches.

Digital Transformation 64

Digital Transformation Data Integration Data Quality Data Warehouse 64

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

Peter James Thomas

MAY 3, 2019

The objective here is to use a variety of techniques to tease out findings from available data (both internal and external) that go beyond the explicit purpose for which it was captured. Control of Data to ensure it is Fit-for-Purpose. Data Architecture / Infrastructure. Best practice has evolved in this area.

Strategy 55

Strategy Data Architecture Data Quality Data Strategy 55

FineReport

MAY 31, 2023

Dupont Analysis Dashboard FineReport simplifies the implementation of the Dupont analysis model, enabling an in-depth examination of an enterprise’s financial condition through Return on Investment (ROI). The Dupont analysis model comprises three key components: profit margin, asset turnover, and equity multiplier.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

Domino Data Lab

JULY 22, 2019

data science’s emergence as an interdisciplinary field – from industry, not academia. why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Andrew White

MARCH 22, 2019

I jest here; what I mean to say is that economics and rational, smart models should trump perfectly designed ideas. This ties into the failure of data governance and MDM (see first item in this list). Too many vendors have convinced their clients they have information stewards when fact they have more data quality analysts.

Analytics 68

Analytics Metadata Data Governance Management 68

erwin

FEBRUARY 19, 2021

A strong data management strategy and supporting technology enables the data quality the business requires, including data cataloging (integration of data sets from various sources), mapping, versioning, business rules and glossaries maintenance and metadata management (associations and lineage). Map data flows.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

Alation

MAY 16, 2023

Machine Learning Data pipelines feed all the necessary data into machine learning algorithms, thereby making this branch of Artificial Intelligence (AI) possible. Data Quality When using a data pipeline, data consistency, quality, and reliability are often greatly improved.

Data Lake 69

Data Lake Data Governance Data Warehouse Data Processing 69

Data Virtualization

MARCH 7, 2024

Reading Time: 3 minutes As we move deeper into 2024, it is imperative for data management leaders to look in their rear-view mirrors to assess and, if needed, refine their data management strategies. One thing is clear; if data-centric organizations want to succeed in.

Management 59

Management Data Integration Strategy Data Lake 59

Data Virtualization

JANUARY 25, 2024

Reading Time: 3 minutes As we head into 2024, it is imperative for data management leaders to look in their rear-view mirrors to assess and, if needed, refine their data management strategies.

Management 59

Management Data Integration Strategy Data Lake 59

Andrew White

JANUARY 11, 2021

Where does the Data Architect role fits in the Operational Model ? Assuming a data architect helps model and guide and assist D&A then they play a key role. This would be part of a Data Literacy program. Decision modeling (one of my favorites). Link Data to Business Outcomes. Fusion teams.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52