AWS Big Data

DECEMBER 21, 2023

AWS Glue provides both visual and code-based interfaces to make data integration effortless. Using a native AWS Glue connector increases agility, simplifies data movement, and improves data quality. For setup instructions, refer to Getting started with Amazon OpenSearch Service.

Analytics 97

Analytics IT Data Lake Visualization 97

DataRobot Blog

MARCH 10, 2022

The first step in building a model that can predict machine failure and even recommend the next best course of action is to aggregate, clean, and prepare data to train against. This task may require complex joins, aggregations, filtering, window functions, and many other data transformations against extremely large-scale data sets.

Manufacturing 52

Manufacturing IoT Machine Learning Forecasting 52

Peter James Thomas

OCTOBER 30, 2018

All the references I can find to it are modern pieces comparing it to the CDO role, so perhaps it is apochryphal. It may well be that one thing that a CDO needs to get going is a data transformation programme. This may purely be focused on cultural aspects of how an organisation records, shares and otherwise uses data.

Marketing 51

Marketing Strategy Data Architecture Data Strategy 51

CIO Business Intelligence

DECEMBER 6, 2023

Airbus was conceiving an ambitious plan to develop an open aviation data platform, Skywise, as a single platform of reference for all major aviation players that would enable them to improve their operational performance and business results and support Airbus’ own digital transformation.

Digital Transformation 113

Digital Transformation Software Cost-Benefit Manufacturing 113

AWS Big Data

FEBRUARY 8, 2023

It’s common to ingest multiple data sources into Amazon Redshift to perform analytics. Often, each data source will have its own processes of creating and maintaining data, which can lead to data quality challenges within and across sources. Answering questions as simple as “How many unique customers do we have?”

Data Quality 78

Data Quality Testing Data Warehouse Unstructured Data 78

Alation

OCTOBER 28, 2021

Protect data at the source. Put data into action to optimize the patient experience and adapt to changing business models. What is Data Governance in Healthcare? Data governance in healthcare refers to how data is collected and used by hospitals, pharmaceutical companies, and other healthcare organizations and service providers.

Data Governance 52

Data Governance Measurement Metrics Data Quality 52

erwin

APRIL 16, 2024

In this blog, we’ll delve into the critical role of governance and data modeling tools in supporting a seamless data mesh implementation and explore how erwin tools can be used in that role. erwin also provides data governance, metadata management and data lineage software called erwin Data Intelligence by Quest.

Metadata 52

Metadata Data Quality Data Governance Modeling 52

Smarten

JANUARY 4, 2018

Extract, Transform and Load (ETL) refers to a process of connecting to data sources, integrating data from various data sources, improving data quality, aggregating it and then storing it in staging data source or data marts or data warehouses for consumption of various business applications including BI, Analytics and Reporting.

Data Warehouse 40

Data Warehouse OLAP Data Governance Optimization 40

DataKitchen

JANUARY 23, 2023

It allows organizations to see how data is being used, where it is coming from, its quality, and how it is being transformed. DataOps Observability includes monitoring and testing the data pipeline, data quality, data testing, and alerting.

Testing 130

Testing Data Governance Data Quality Data-driven 130

Alation

NOVEMBER 22, 2022

What Is Data Governance In The Public Sector? Effective data governance for the public sector enables entities to ensure data quality, enhance security, protect privacy, and meet compliance requirements. With so much focus on compliance, democratizing data for self-service analytics can present a challenge.

Data Governance 52

Data Governance Metadata Data-driven Unstructured Data 52

Jet Global

MAY 28, 2019

A data warehouse is typically used by companies with a high level of data diversity or analytical requirements. When you want to get answers from your data, your request goes directly to the appropriate cube. When organizations start to collect data in multiple databases, the size of the data sets grow exponentially.

Data Warehouse 85

Data Warehouse Reporting Business Intelligence Sales 85

Jet Global

FEBRUARY 23, 2024

The quick and dirty definition of data mapping is the process of connecting different types of data from various data sources. Data mapping is a crucial step in data modeling and can help organizations achieve their business goals by enabling data integration, migration, transformation, and quality.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Jet Global

MAY 9, 2024

Data Extraction : The process of gathering data from disparate sources, each of which may have its own schema defining the structure and format of the data and making it available for processing. 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