Ontotext

MAY 2, 2024

Storage-centric approach In the storage-centric approach, people try to address data silos by throwing everything in a data lake or a data warehouse. But, although, this helps somewhat in terms of architecture, soon these data lakes become unwieldy. Another complication was the existing data silos.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

AWS Big Data

MARCH 26, 2024

Without C360, businesses face missed opportunities, inaccurate reports, and disjointed customer experiences, leading to customer churn. Profile aggregation – When you’ve uniquely identified a customer, you can build applications in Managed Service for Apache Flink to consolidate all their metadata, from name to interaction history.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

AWS Big Data

NOVEMBER 29, 2023

Zero-ETL integration also enables you to load and analyze data from multiple operational database clusters in a new or existing Amazon Redshift instance to derive holistic insights across many applications. Use one click to access your data lake tables using auto-mounted AWS Glue data catalogs on Amazon Redshift for a simplified experience.

Data Warehouse 101

Data Warehouse Data Lake Analytics Machine Learning 101

AWS Big Data

MARCH 27, 2023

Developers, data scientists, and analysts can work across databases, data warehouses, and data lakes to build reporting and dashboarding applications, perform real-time analytics, share and collaborate on data, and even build and train machine learning (ML) models with Redshift Serverless.

Data Warehouse 86

Data Warehouse Management Snapshot Data Lake 86

AWS Big Data

DECEMBER 18, 2023

AWS Step Functions is a fully managed visual workflow service that enables you to build complex data processing pipelines involving a diverse set of extract, transform, and load (ETL) technologies such as AWS Glue , Amazon EMR , and Amazon Redshift. There are multiple tables related to customers and order data in the RDS database.

Metadata 121

Metadata Visualization Data Lake Data-driven 121

erwin

OCTOBER 8, 2020

These tools range from enterprise service bus (ESB) products, data integration tools; extract, transform and load (ETL) tools, procedural code, application program interfaces (APIs), file transfer protocol (FTP) processes, and even business intelligence (BI) reports that further aggregate and transform data.

Data Governance 145

Data Governance Metadata Testing Data Lake 145

CIO Business Intelligence

SEPTEMBER 22, 2023

Data management platform definition A data management platform (DMP) is a suite of tools that helps organizations to collect and manage data from a wide array of first-, second-, and third-party sources and to create reports and build customer profiles as part of targeted personalization campaigns.

Management 96

Management Advertising Data Lake Sales 96

CIO Business Intelligence

JUNE 9, 2022

A data management platform (DMP) is a group of tools designed to help organizations collect and manage data from a wide array of sources and to create reports that help explain what is happening in those data streams. Deploying a DMP can be a great way for companies to navigate a business world dominated by data.

Management 136

Management Advertising Data Lake Sales 136

AWS Big Data

DECEMBER 21, 2023

The data products used inside the company include insights from user journeys, operational reports, and marketing campaign results, among others. The data platform serves on average 60 thousand queries per day. The data volume is in double-digit TBs with steady growth as business and data sources evolve.

Data Lake 89

Data Lake Data Warehouse Data-driven B2B 89

CIO Business Intelligence

DECEMBER 21, 2022

BI software helps companies do just that by shepherding the right data into analytical reports and visualizations so that users can make informed decisions. Determining which BI delivery method fits best There are many traditional IT-managed ways to deliver reports and insights from data.

IT 122

IT Business Intelligence Sales Key Performance Indicator 122

AWS Big Data

MARCH 7, 2023

A data hub contains data at multiple levels of granularity and is often not integrated. It differs from a data lake by offering data that is pre-validated and standardized, allowing for simpler consumption by users. Data hubs and data lakes can coexist in an organization, complementing each other.

Analytics 72

Analytics Data Warehouse Data Lake Metadata 72

Cloudera

JANUARY 21, 2021

Does your organization’s success depend on immediate delivery of new reports, applications, or projects? Storing data in a proprietary, single-workload solution also recreates dangerous data silos all over again, as it locks out other types of workloads over the same shared data. Do you need faster time to value?

Data Lake 93

Data Lake Data Warehouse IT Analytics 93

Jet Global

FEBRUARY 23, 2024

Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation. Data mapping helps standardize, visualize, and understand data across different systems and applications.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Alation

JUNE 21, 2022

Analysts didn’t just want to catalog data sources, they wanted to include dashboards, reports, and visualizations. Why start with a data source and build a visualization, if you can just find a visualization that already exists, complete with metadata about it?

Metadata 52

Metadata Data Quality Visualization Data Lake 52

Alation

MARCH 29, 2021

To keep up, more businesses have shifted toward data-driven decision making. According to a NewVantage Partners Report , 96% of executives indicate that their organization aspires to a data-driven culture, while only 24% report success. In this blog, we will discuss how data catalogs accelerate search & discovery.

Metadata 59

Metadata Data-driven Enterprise Machine Learning 59

IBM Big Data Hub

OCTOBER 12, 2023

Among the tasks necessary for internal and external compliance is the ability to report on the metadata of an AI model. Metadata includes details specific to an AI model such as: The AI model’s creation (when it was created, who created it, etc.)

Cost-Benefit 77

Cost-Benefit Metadata Data Governance Modeling 77

AWS Big Data

APRIL 25, 2024

In the era of data, organizations are increasingly using data lakes to store and analyze vast amounts of structured and unstructured data. Data lakes provide a centralized repository for data from various sources, enabling organizations to unlock valuable insights and drive data-driven decision-making.

Optimization 65

Optimization Data Lake Cost-Benefit Reporting 65

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. Technical metadata to describe schemas, indexes and other database objects.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Cloudera

JANUARY 15, 2021

The results demonstrate superior price performance of Cloudera Data Warehouse on the full set of 99 queries from the TPC-DS benchmark. DW1 is an anonymized cloud data warehouse running on AWS and DW2 is an anonymized data warehouse running on GCP. Cluster size details for other vendors can be found in the McKnight report.

Data Warehouse 94

Data Warehouse Cost-Benefit Consulting Interactive 94

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. Business intelligence reports. Visualizations. It also provides a catalog of datasets, including data analysis and visualization features.

Enterprise 52

Enterprise Metadata Data Governance Visualization 52

Alation

FEBRUARY 17, 2023

Reichental describes data governance as the overarching layer that empowers people to manage data well ; as such, it is focused on roles & responsibilities, policies, definitions, metrics, and the lifecycle of the data. In this way, data governance is the business or process side. This is a very good thing.

Data Governance 52

Data Governance Data Quality Metadata Cost-Benefit 52

Alation

FEBRUARY 13, 2020

A typical data catalog implementation process begins by defining the business and technical case, proceeds through technology selection and installation, then moves on to data discovery and populating the metadata catalog. Figure 1 – Data Catalog Implementation. Who needs data literacy training? See figure 1.)

Metadata 52

Metadata Data Governance Cost-Benefit Visualization 52

Ontotext

MARCH 8, 2023

Rich metadata and semantic modeling continue to drive the matching of 50K training materials to specific curricula, leading new, data-driven, audience-based marketing efforts that demonstrate how the recommender service is achieving increased engagement and performance from over 2.3 million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Domino Data Lab

APRIL 3, 2019

Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. in lieu of simply landing in a data lake.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Domino Data Lab

AUGUST 8, 2019

He’s been out of Wolfram for a while and writing exquisite science books including Elements: A Visual Explanation of Every Known Atom in the Universe and Molecules: The Architecture of Everything. The gist is, leveraging metadata about research datasets, projects, publications, etc., Rinse, lather, repeat—probably each week.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

Andrew White

JANUARY 11, 2021

What is unique about the D&A Leadership Vision is that it crossed over into business since for many organizations, the CDO reports into the CEO or COO (as examples). The fill report is here: Leadership Vision for 2021: Data and Analytics. CAO, and even where the CAO reports into a different organization.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52