Alation

JANUARY 26, 2023

That’s why many organizations invest in technology to improve data processes, such as a machine learning data pipeline. However, data needs to be easily accessible, usable, and secure to be useful — yet the opposite is too often the case. How can data engineers address these challenges directly?

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

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 77

Metadata Data Lake Data Processing Data-driven 77

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 127

Data Architecture Data Warehouse Statistics Visualization 127

Alation

FEBRUARY 13, 2020

Human Curation + Machine Learning. The way Herschel, Fry, and Zimmerman talked about AI in many respects reflects our vision for machine learning data catalogs. What’s more, Zaidi and Gartner believe that this vision of a machine-learning-enabled data catalog creates real value for enterprises.

Machine Learning 52

Machine Learning Data Analytics Analytics Metadata 52

AWS Big Data

APRIL 29, 2024

The construction of big data applications based on open source software has become increasingly uncomplicated since the advent of projects like Data on EKS , an open source project from AWS to provide blueprints for building data and machine learning (ML) applications on Amazon Elastic Kubernetes Service (Amazon EKS).

Management 98

Management Big Data Metadata Data Warehouse 98

Alation

FEBRUARY 13, 2020

In an earlier blog, I defined a data catalog as “a collection of metadata, combined with data management and search tools, that helps analysts and other data users to find the data that they need, serves as an inventory of available data, and provides information to evaluate fitness data for intended uses.”.

Metadata 52

Metadata Management Data Lake Data Governance 52

Octopai

NOVEMBER 5, 2019

Is your data going somewhere? No, we’re not talking about databases going AWOL or data warehouses getting a little R&R at the beach. We’re talking about migrations from one system to another, or combining data from different systems into a single system or warehouse. Data Dictionaries.

Machine Learning 44

Machine Learning Metadata Data Governance Data Warehouse 44

AWS Big Data

OCTOBER 4, 2023

Collaboration – Analysts, data scientists, and data engineers often own different steps within the end-to-end analytics journey but do not have an simple way to collaborate on the same governed data, using the tools of their choice. Automate data discovery and cataloging with machine learning (ML).

Metadata 102

Metadata Data Lake Publishing Data Governance 102

Octopai

APRIL 24, 2023

This new native integration enhances our data lineage solution by providing seamless integration with one of the most powerful cloud-based data warehouses, benefiting data teams and enabling support for a broader range of data lineage, discovery, and catalog.

Cost-Benefit 96

Cost-Benefit Data-driven Data Warehouse Data Governance 96

Alation

AUGUST 30, 2022

We continue to make deep investments in governance, including new capabilities in the Stewardship Workbench, a core part of the Data Governance App. Centralization of metadata. A decade ago, metadata was everywhere. Consequently, useful metadata was unfindable and unusable. Then Alation came along.

Metadata 52

Metadata Data Quality Data Governance Machine Learning 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. A data hub contains data at multiple levels of granularity and is often not integrated.

Analytics 74

Analytics Data Warehouse Data Lake Metadata 74

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 81

Management Metadata Data Architecture Data Lake 81

AWS Big Data

MARCH 26, 2024

In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges. Then, you transform this data into a concise format. Let’s find out what role each of these components play in the context of C360.

Data Strategy 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

Alation

OCTOBER 21, 2021

But, on the back end, data lakes give businesses a common repository to collect and store data, streamlined usage from a single source, and access to the raw data necessary for today’s advanced analytics and artificial intelligence (AI) needs. A frequent and periodic data cleansing strategy is. Lack of metadata.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

CIO Business Intelligence

DECEMBER 21, 2022

Stout, for instance, explains how Schellman addresses integrating its customer relationship management (CRM) and financial data. “A A lot of business intelligence software pulls from a data warehouse where you load all the data tables that are the back end of the different software,” she says. “Or

IT 127

IT Business Intelligence Sales Key Performance Indicator 127

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 84

Data Lake Data Governance Data Architecture Machine Learning 84

IBM Big Data Hub

AUGUST 4, 2023

Data democratization instead refers to the simplification of all processes related to data, from storage architecture to data management to data security. It also requires an organization-wide data governance approach, from adopting new types of employee training to creating new policies for data storage.

Data Architecture 60

Data Architecture Data Lake Machine Learning Data Governance 60

Alation

DECEMBER 15, 2022

June 2017: Dresner Advisory Services names Alation the #1 data catalog in its inaugural Data Catalog End-User Market Study. August 2017: Alation debuts as a leader in the Gartner MQ for Metadata Management Solutions. August 2018: Gartner names Alation a 2X Leader in the MQ for Metadata Management Solutions.

Metadata 52

Metadata Data Governance Data Quality Marketing 52

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. Sometimes, these outputs are biased because the data used to train the model was incomplete or inaccurate in some way. And that makes sense.

Cost-Benefit 78

Cost-Benefit Metadata Data Governance Modeling 78

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

Alation

AUGUST 11, 2022

The data warehouse and analytical data stores moved to the cloud and disaggregated into the data mesh. Today, the brightest minds in our industry are targeting the massive proliferation of data volumes and the accompanying but hard-to-find value locked within all that data. Architectures became fabrics.

Metadata 52

Metadata Data Warehouse Data Quality Data Lake 52

Alation

AUGUST 26, 2021

What Is Data Intelligence? Data intelligence is a system to deliver trustworthy, reliable data. It includes intelligence about data, or metadata. IDC coined the term, stating, “data intelligence helps organizations answer six fundamental questions about data.” Why keep data at all?

Metadata 64

Metadata Data Governance Dashboards Software 64

Alation

FEBRUARY 13, 2020

Key analyst firms like Forrester, Gartner, and 451 Research have cited “ soaring demands from data catalogs ”, pondered whether data catalogs are the “ most important breakthrough in analytics to have emerged in the last decade ,” and heralded the arrival of a brand new market: Machine Learning Data Catalogs.

Metadata 52

Metadata Machine Learning Data Governance Reporting 52

Alation

FEBRUARY 13, 2020

Data curation is important in today’s world of data sharing and self-service analytics, but I think it is a frequently misused term. When speaking and consulting, I often hear people refer to data in their data lakes and data warehouses as curated data, believing that it is curated because it is stored as shareable data.

Metadata 52

Metadata Data Warehouse Data Lake Data Governance 52

Alation

APRIL 14, 2022

Semantics, context, and how data is tracked and used mean even more as you stretch to reach post-migration goals. This is why, when data moves, it’s imperative for organizations to prioritize data discovery. Data discovery is also critical for data governance , which, when ineffective, can actually hinder organizational growth.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. Doesn’t this seem like a worthy goal for machine learning—to make the machines learn to work more effectively?

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

AWS Big Data

SEPTEMBER 25, 2023

With Amazon Redshift , you can run a complex mix of workloads on your data warehouse, such as frequent data loads running alongside business-critical dashboard queries and complex transformation jobs. We also see more and more data science and machine learning (ML) workloads.

Management 97

Management Data Warehouse Metrics Dashboards 97

Alation

AUGUST 11, 2021

The three of us talked migration strategy and the best way to move to the Snowflake Data Cloud. As Vice President of Data Governance at TMIC, Anthony has robust experience leading cloud migration as part of a larger data strategy. Creating an environment better suited for data governance. The Plan in Action.

Data Governance 52

Data Governance Insurance Metadata Strategy 52

AWS Big Data

MARCH 10, 2023

However, as data processing at scale solutions grow, organizations need to build more and more features on top of their data lakes. Additionally, the task of maintaining and managing files in the data lake can be tedious and sometimes complex. The Iceberg table is synced with the AWS Glue Data Catalog.

Data Lake 105

Data Lake Sales Data Warehouse Snapshot 105

Alation

FEBRUARY 13, 2020

Why do we need a data catalog? What does a data catalog do? These are all good questions and a logical place to start your data cataloging journey. Data catalogs have become the standard for metadata management in the age of big data and self-service analytics. Figure 1 – Data Catalog Metadata Subjects.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

Ontotext

MARCH 18, 2020

The many data warehouse systems designed in the last 30 years present significant difficulties in that respect. When designing a system’s architecture, it’s impossible to know from the start all the ways data will be used. The third challenge is how to combine data management with analytics.

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

Cloudera

MAY 12, 2021

Use cases could include but are not limited to: predictive maintenance, log data pipeline optimization, connected vehicles, industrial IoT, fraud detection, patient monitoring, network monitoring, and more. DATA FOR ENTERPRISE AI. SECURITY AND GOVERNANCE LEADERSHIP.

Digital Transformation 68

Digital Transformation Machine Learning Optimization Data Lake 68

Alation

JUNE 30, 2022

We are now seeing a similar transformation in the world of data, where there’s tension between the old world (single-source-of-truth data warehouses with top-down data governance) and the new world (distributed, self-service analytics with grassroots management). Data quality can change with time.

Metadata 52

Metadata Data Warehouse Data Quality Data-driven 52

Jet Global

FEBRUARY 23, 2024

This includes cleaning, aggregating, enriching, and restructuring data to fit the desired format. Load : Once data transformation is complete, the transformed data is loaded into the target system, such as a data warehouse, database, or another application.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

IBM Big Data Hub

MARCH 14, 2024

This involves unifying and sharing a single copy of data and metadata across IBM® watsonx.data ™, IBM® Db2 ®, IBM® Db2® Warehouse and IBM® Netezza ®, using native integrations and supporting open formats, all without the need for migration or recataloging.

Cost-Benefit 77

Cost-Benefit Metadata Optimization Management 77

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