Alation

DECEMBER 15, 2022

March 2015: Alation emerges from stealth mode to launch the first official data catalog to empower people in enterprises to easily find, understand, govern and use data for informed decision making that supports the business. May 2016: Alation named a Gartner Cool Vendor in their Data Integration and Data Quality, 2016 report.

Metadata 52

Metadata Data Governance Data Quality Marketing 52

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 69

Analytics Data Warehouse Data Lake Metadata 69

IBM Big Data Hub

MAY 9, 2022

Data governance and privacy. Data privacy laws such as the GDPR in the EU, CCPA in California and PIPEDA in Canada have been enacted at the same time businesses are revitalizing efforts to establish data quality, not just data volume. Poor data quality costs organizations an average of $12.9

Management 57

Management Data Quality Metadata Data Integration 57

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 68

Data Quality Data Integration Metadata Cost-Benefit 68

Sanjeev Mohan

FEBRUARY 6, 2019

Then in the middle of 2017, a realization set in that we were one year away from GDPR and needed to focus on data governance. I ended up writing two documents on data governance. As you can tell, data governance is a hot topic but an area that many public cloud vendors are weak in.

Data Analytics 49

Data Analytics Analytics Data Governance Experimentation 49

AWS Big Data

APRIL 19, 2023

Background The success of a data-driven organization recognizes data as a key enabler to increase and sustain innovation. The goal of a data product is to solve the long-standing issue of data silos and data quality. The data science algorithm Valentine is an effective tool for this.

Technology 80

Technology Data-driven Machine Learning Sales 80

Andrew White

JULY 5, 2023

.” This is not much of catalog at all, and is closer to being a D&A governance solution and stewardship solution. When a business analyst or data science leader is building a model, they will often start out by searching a catalog for data. They WOULD have some opportunity to govern the glossary!

Metrics 52

Metrics Metadata Modeling Data Quality 52

Domino Data Lab

OCTOBER 1, 2020

This data supports all kinds of use cases within organizations, from helping production analysts understand how production is progressing, to allowing research scientists to look at the results of a set of treatments across different trials and cross-sections of the population.

Enterprise 105

Enterprise Metadata Cost-Benefit Data Processing 105

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

O'Reilly on Data

JULY 28, 2020

There’s a substantial literature about ethics, data, and AI, so rather than repeat that discussion, we’ll leave you with a few resources. Ethics and Data Science is a short book that helps developers think through data problems, and includes a checklist that team members should revisit throughout the process.

Marketing 362

Marketing Experimentation Metrics Testing 362

Octopai

DECEMBER 12, 2021

What enables you to use all those gigabytes and terabytes of data you’ve collected? Metadata is the pertinent, practical details about data assets: what they are, what to use them for, what to use them with. Without metadata, data is just a heap of numbers and letters collecting dust. Where does metadata come from?

Metadata 93

Metadata Management Data Quality Data Governance 93

Peter James Thomas

AUGUST 29, 2018

I have since run and driven transformation in Reference Data, Master Data , KYC [3] , Customer Data, Data Warehousing and more recently Data Lakes and Analytics , constantly building experience and capability in the Data Governance , Quality and data services domains, both inside banks, as a consultant and as a vendor.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61

TDAN

NOVEMBER 3, 2020

In the September issue of TDAN.com, Anthony Algmin denounced Data Catalogs as a “1980’s solution to a 2020’s problem.” What is the state of data science today? As I state in my book, The Data Catalog: Sherlock Holmes Sleuthing for Data Analytics and in many articles, 80% (or more) of a data analyst’s […].

Data Science 59

Data Science Data Analytics Analytics Data Quality 59

IBM Big Data Hub

JANUARY 17, 2023

Essential components of a data lakehouse architecture and what makes an open data lakehouse. At the core of a data lakehouse architecture includes the storage, metadata service and the query engine, and typically a data governance component made up of a policy engine and a data dictionary.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

O'Reilly on Data

MARCH 18, 2020

Whether it’s controlling for common risk factors—bias in model development, missing or poorly conditioned data, the tendency of models to degrade in production—or instantiating formal processes to promote data governance, adopters will have their work cut out for them as they work to establish reliable AI production lines.

Enterprise 311

Enterprise Deep Learning Data Governance Risk 311

IBM Big Data Hub

JANUARY 17, 2023

IBM Cloud Pak for Data Express solutions offer clients a simple on ramp to start realizing the business value of a modern architecture. Data governance. The data governance capability of a data fabric focuses on the collection, management and automation of an organization’s data. Start a trial.

Data-driven 57

Data-driven Enterprise Data Governance Prescriptive Analytics 57

IBM Big Data Hub

APRIL 27, 2022

Gartner defines a data fabric as “a design concept that serves as an integrated layer of data and connecting processes. The data fabric architectural approach can simplify data access in an organization and facilitate self-service data consumption at scale. What’s a data mesh? 11 May 2021. .

Management 87

Management Metadata Data Architecture Data Lake 87

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 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

Data Virtualization

AUGUST 4, 2022

Reading Time: 3 minutes Last month, IDC announced that LeasePlan, a car-as-a-service company, was the winner of IDC’s European Data Strategy and Innovation awards, in the category of Data Management Excellence, for LeasePlan’s logical data fabric. This is a testament to the maturity of.

Data Strategy 52

Data Strategy Data Integration Strategy Management 52

Alation

JULY 28, 2022

For this redesign to succeed, it is critical to remember data governance becomes even more essential to understanding where your data is at all times. What Are the Biggest Business Risks to Cloud Data Migration? Like any data migration, cloud data migration requires careful planning, design, and execution.

Data Warehouse 69

Data Warehouse Cost-Benefit Data Governance Data-driven 69

Alation

SEPTEMBER 23, 2021

What Is a Data Catalog? A data catalog is a centralized storage bank of metadata on information sources from across the enterprise, such as: Datasets. The data catalog also stores metadata (data about data, like a conversation), which gives users context on how to use each asset. Data Catalog by Type.

Enterprise 52

Enterprise Metadata Data Governance Visualization 52

Octopai

JANUARY 19, 2021

Octopai can fully map the BI landscape and trace metadata movement in a mixed environment including complex multi-vendor landscapes. Octopai’s cloud-based offerings hasten data delivery and allow full automation to dramatically accelerate the entire BI data lifecycle.

Metadata 52

Metadata ROI Optimization Data Quality 52

Andrew White

JANUARY 9, 2022

This research does not tell you where to do the work; it is meant to provide the questions to ask in order to work out where to target the work, spanning reporting/analytics (classic), advanced analytics and data science (lab), data management and infrastructure, and D&A governance. We write about data and analytics.

Analytics 64

Analytics Measurement Modeling Data-driven 64

Alation

DECEMBER 15, 2021

Yet high-volume collection makes keeping that foundation sound a challenge, as the amount of data collected by businesses is greater than ever before. An effective data governance strategy is critical for unlocking the full benefits of this information. Data governance requires a system.

Data Governance 52

Data Governance Strategy Metadata Data Strategy 52

Alation

FEBRUARY 17, 2023

This past week, I had the pleasure of hosting Data Governance for Dummies author Jonathan Reichental for a fireside chat , along with Denise Swanson , Data Governance lead at Alation. Can you have proper data management without establishing a formal data governance program?

Data Governance 52

Data Governance Data Quality Metadata Cost-Benefit 52

Rocket-Powered Data Science

MARCH 20, 2023

Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science. Datasphere is not just for data managers. As you would guess, maintaining context relies on metadata.

Data Warehouse 324

Data Warehouse Metadata Digital Transformation Unstructured Data 324

O'Reilly on Data

DECEMBER 19, 2018

We need to do more than automate model building with autoML; we need to automate tasks at every stage of the data pipeline. In a previous post , we talked about applications of machine learning (ML) to software development, which included a tour through sample tools in data science and for managing data infrastructure.

Machine Learning 261

Machine Learning Software Testing Metadata 261

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. This ties into the failure of data governance and MDM (see first item in this list).

Analytics 68

Analytics Metadata Data Governance Management 68

Andrew White

JANUARY 11, 2021

As such a head of analytics, BI and data science may emerge. Are you anticipating continued separation of “BI/Analytics” teams from “Data Science” teams or are those roles merging in the years ahead? Many data science labs are set up as shared services. That’s the idea.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Alation

FEBRUARY 13, 2020

You see scale, obviously data science work in the cloud. What’s going on with the whole data at the center? One is that idea of the center and the other is your point about data quality and data trust. The other thing in terms of that data quality and data trustworthiness has been a differentiator.

ROI 52

ROI Data-driven Finance Data Quality 52

Jet Global

MARCH 14, 2024

The solution offers data movement, data science, real-time analytics, and business intelligence within a single platform. Jet’s interface lets you handle data administration easily, without advanced coding skills. You don’t need technical skills to manage complex data workflows in the Fabric environment.

Analytics 52

Analytics Management Reporting Enterprise 52