AWS Big Data

JUNE 6, 2023

AWS Glue is a serverless data integration service that makes it simple to discover, prepare, and combine data for analytics, machine learning (ML), and application development. Hundreds of thousands of customers use data lakes for analytics and ML to make data-driven business decisions.

Data Quality 76

Data Quality Data Lake Data-driven Metrics 76

AWS Big Data

FEBRUARY 1, 2023

With data volumes exhibiting a double-digit percentage growth rate year on year and the COVID pandemic disrupting global logistics in 2021, it became more critical to scale and generate near-real-time data. You can visually create, run, and monitor extract, transform, and load (ETL) pipelines to load data into your data lakes.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

AWS Big Data

JULY 13, 2023

Data quality for account and customer data – Altron wanted to enable data quality and data governance best practices. Goals – Lay the foundation for a data platform that can be used in the future by internal and external stakeholders. Basic formatting and readability of the data is standardized here.

Optimization 91

Optimization B2B Data Quality Sales 91

Alation

MAY 16, 2023

Data Pipeline Use Cases Here are just a few examples of the goals you can achieve with a robust data pipeline: Data Prep for Visualization Data pipelines can facilitate easier data visualization by gathering and transforming the necessary data into a usable state.

Data Lake 69

Data Lake Data Governance Data Warehouse Data Processing 69

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.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

AWS Big Data

JUNE 12, 2023

Acting as a bridge between producer and consumer apps, it enforces the schema, reduces the data footprint in transit, and safeguards against malformed data. AWS Glue is an ideal solution for running stream consumer applications, discovering, extracting, transforming, loading, and integrating data from multiple sources.

Management 80

Management Metadata Testing Internet of Things 80

Alation

MAY 16, 2023

Data Pipeline Use Cases Here are just a few examples of the goals you can achieve with a robust data pipeline: Data Prep for Visualization Data pipelines can facilitate easier data visualization by gathering and transforming the necessary data into a usable state.

Data Lake 40

Data Lake Data Governance Data Warehouse Data Processing 40

AWS Big Data

JULY 12, 2023

Amazon Redshift helps you break down the data silos and allows you to run unified, self-service, real-time, and predictive analytics on all data across your operational databases, data lake, data warehouse, and third-party datasets with built-in governance. This is often a laborious and error-prone process.

Data Warehouse 52

Data Warehouse Modeling Dashboards Data Lake 52

CIO Business Intelligence

MARCH 22, 2022

Which type(s) of storage consolidation you use depends on the data you generate and collect. . One option is a data lake—on-premises or in the cloud—that stores unprocessed data in any type of format, structured or unstructured, and can be queried in aggregate. Set up unified data governance rules and processes.

Analytics 101

Analytics Key Performance Indicator Data Warehouse Data-driven 101

Ontotext

FEBRUARY 26, 2024

Firstly, on the data maturity spectrum, the vast majority of organizations I’ve spoken with are stuck in the information stage. They have massive amounts of data they’re collecting and storing in their relational databases, document stores, data lakes, and data warehouses. RDF vs LPG?

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

erwin

AUGUST 31, 2023

Improved Decision Making : Well-modeled data provides insights that drive informed decision-making across various business domains, resulting in enhanced strategic planning. Reduced Data Redundancy : By eliminating data duplication, it optimizes storage and enhances data quality, reducing errors and discrepancies.

Data-driven 98

Data-driven Modeling Enterprise Structured Data 98

IBM Big Data Hub

AUGUST 4, 2023

In turn, they both must also have the data literacy skills to be able to verify the data’s accuracy, ensure its security, and provide or follow guidance on when and how it should be used. Then, it applies these insights to automate and orchestrate the data lifecycle.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

erwin

JULY 17, 2019

Outsourcing these data management efforts to professional services firms only delays schedules and increases costs. With automation, data quality is systemically assured. The data pipeline is seamlessly governed and operationalized to the benefit of all stakeholders. Digital Transformation Strategy: Smarter Data.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

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

Jet Global

FEBRUARY 23, 2024

Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. This can involve moving data between different storage systems, databases, or applications.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52