Ontotext

NOVEMBER 16, 2023

In a data mesh, domains are represented by a node, which can be an operational data store (ODS), a data warehouse, or a data lake tailored to the domain’s requirements. Don’t Forget Team Structure Team and organizational structure are an important aspect to consider for data mesh.

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

Alation

JANUARY 26, 2023

Below are some examples of common data governance goals: All data collection, storage, and usage must meet the terms of legislation. Avoid fines that could result from issues such as data leakage or lack of data minimization practices. This is “table stakes” for any data governance program!).

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

Alation

FEBRUARY 13, 2020

Figure 1 illustrates the typical metadata subjects contained in a data catalog. Figure 1 – Data Catalog Metadata Subjects. Datasets are the files and tables that data workers need to find and access. They may reside in a data lake, warehouse, master data repository, or any other shared data resource.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

Cloudera

FEBRUARY 16, 2022

Each workspace is associated with a collection of cloud resources. In the case of CDP Public Cloud, this includes virtual networking constructs and the data lake as provided by a combination of a Cloudera Shared Data Experience (SDX) and the underlying cloud storage. The highest level construct in CML is a workspace.

Machine Learning 85

Machine Learning Modeling Metadata Recreation/Entertainment 85

Cloudera

JANUARY 21, 2021

While cloud-native, point-solution data warehouse services may serve your immediate business needs, there are dangers to the corporation as a whole when you do your own IT this way. Cloudera Data Warehouse (CDW) is here to save the day! CDW is an integrated data warehouse service within Cloudera Data Platform (CDP).

Data Lake 95

Data Lake Data Warehouse IT Analytics 95

Cloudera

AUGUST 30, 2022

Data Lakehouse: Data lakehouses integrate and unify the capabilities of data warehouses and data lakes, aiming to support artificial intelligence, business intelligence, machine learning, and data engineering use cases on a single platform. Towards Data Science ). Forrester ). Gartner ).

Data Architecture 80

Data Architecture Data Lake Metadata Data Warehouse 80

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. We recommend building your data strategy around five pillars of C360, as shown in the following figure.

Data Strategy 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

Alation

MAY 16, 2023

Sources can include analytics data regarding user behavior, transactional data from ecommerce websites, and third-party data from other organizations. It’s worth noting that a data pipeline may have more than one data source. Ingestion tools are connected to various data sources.

Data Lake 69

Data Lake Data Governance Data Warehouse Data Processing 69

AWS Big Data

FEBRUARY 21, 2023

Data warehouses play a vital role in healthcare decision-making and serve as a repository of historical data. A healthcare data warehouse can be a single source of truth for clinical quality control systems. What is a dimensional data model? What is a dimensional data model? What is a data vault?

Data Warehouse 64

Data Warehouse Data Lake Cost-Benefit Modeling 64

Alation

MAY 16, 2023

Sources can include analytics data regarding user behavior, transactional data from ecommerce websites, and third-party data from other organizations. It’s worth noting that a data pipeline may have more than one data source. Ingestion tools are connected to various data sources.

Data Lake 40

Data Lake Data Governance Data Warehouse Data Processing 40

CIO Business Intelligence

SEPTEMBER 22, 2023

All this data arrives by the terabyte, and a data management platform can help marketers make sense of it all. DMPs excel at negotiating with a wide array of databases, data lakes, or data warehouses, ingesting their streams of data and then cleaning, sorting, and unifying the information therein.

Management 105

Management Advertising Data Lake Sales 105

CIO Business Intelligence

JUNE 9, 2022

All this data arrives by the terabyte, and a data management platform can help marketers make sense of it all. Marketing-focused or not, DMPs excel at negotiating with a wide array of databases, data lakes, or data warehouses, ingesting their streams of data and then cleaning, sorting, and unifying the information therein.

Management 144

Management Advertising Data Lake Sales 144

Cloudera

DECEMBER 16, 2022

Cloudera has long had the capabilities of a data lakehouse, if not the label. Cloudera enables an open data lakehouse architecture that combines all the flexibility of the data lake with the performance of the data warehouse, so enterprises can use all data — both structured and unstructured.

Management 92

Management Metadata Machine Learning Data Lake 92

datapine

AUGUST 29, 2022

The new edition also explores artificial intelligence in more detail, covering topics such as Data Lakes and Data Sharing practices. 6) Lean Analytics: Use Data to Build a Better Startup Faster, by Alistair Croll and Benjamin Yoskovitz.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Alation

FEBRUARY 13, 2020

More often than not, today, the key to unlocking that accomplishment sits within a tsunami of data: data collected from consumers, applications, and sensors. Each of your organizations has something impossible to accomplish. I don’t know exactly what it is, but I know it’s there.

Machine Learning 52

Machine Learning Data-driven Big Data Technology 52

IBM Big Data Hub

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. Then, it applies these insights to automate and orchestrate the data lifecycle.

Data Architecture 65

Data Architecture Data Lake Machine Learning Data Governance 65

erwin

JULY 17, 2019

Once you’ve determined what part(s) of your business you’ll be innovating — the next step in a digital transformation strategy is using data to get there. Constructing A Digital Transformation Strategy: Data Enablement. Many organizations prioritize data collection as part of their digital transformation strategy.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

Cloudera

NOVEMBER 22, 2021

In legacy analytical systems such as enterprise data warehouses, the scalability challenges of a system were primarily associated with computational scalability, i.e., the ability of a data platform to handle larger volumes of data in an agile and cost-efficient way. Introduction. CRM platforms). CRM platforms).

Data Processing 94

Data Processing Data Warehouse Enterprise Visualization 94

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52