AWS Big Data

DECEMBER 21, 2023

AWS Glue is a serverless data integration service that makes it straightforward to discover, prepare, and combine data for analytics, machine learning (ML), and application development. AWS Glue provides both visual and code-based interfaces to make data integration effortless.

Analytics 96

Analytics IT Data Lake Visualization 96

DataRobot Blog

MARCH 10, 2022

With Snowflake’s newest feature release, Snowpark , developers can now quickly build and scale data-driven pipelines and applications in their programming language of choice, taking full advantage of Snowflake’s highly performant and scalable processing engine that accelerates the traditional data engineering and machine learning life cycles.

Manufacturing 52

Manufacturing IoT Machine Learning Forecasting 52

Sisense

OCTOBER 15, 2020

As real-time analytics and machine learning stream processing are growing rapidly, they introduce a new set of technological and conceptual challenges. Every data professional knows that ensuring data quality is vital to producing usable query results.

Dashboards 98

Dashboards IoT Optimization Internet of Things 98

CIO Business Intelligence

DECEMBER 22, 2022

Where DataOps fits Enterprises today are increasingly injecting machine learning into a vast array of products and services and DataOps is an approach geared toward supporting the end-to-end needs of machine learning. The DataOps approach is not limited to machine learning,” they add.

Analytics 128

Analytics Machine Learning Software Data Quality 128

AWS Big Data

JULY 20, 2023

One key component that plays a central role in modern data architectures is the data lake, which allows organizations to store and analyze large amounts of data in a cost-effective manner and run advanced analytics and machine learning (ML) at scale. This ensures that the data is suitable for training purposes.

Data Lake 88

Data Lake Analytics Snapshot Optimization 88

Alation

AUGUST 11, 2022

But there are only so many data engineers available in the market today; there’s a big skills shortage. So to get away from that lack of data engineers, what data mesh says is, ‘Take those business logic data transformation capabilities and move that to the domains.’ Let’s take data privacy as an example.

Metadata 52

Metadata Data Warehouse Data Quality Data Lake 52

IBM Big Data Hub

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

Cost-Benefit 76

Cost-Benefit Metadata Optimization Management 76

Octopai

JANUARY 19, 2021

With Octopai’s support and analysis of Azure Data Factory, enterprises can now view complete end-to-end data lineage from Azure Data Factory all the way through to reporting for the first time ever. The post NEW: Octopai Announces Support of Microsoft Azure Data Factory appeared first on Octopai.

Metadata 52

Metadata ROI Optimization Data Quality 52

DataKitchen

APRIL 26, 2021

Hodges commented, “Our first focus was to up our game around data quality and lowering errors in production. Workiva also prioritized improving the data lifecycle of machine learning models, which otherwise can be very time consuming for the team to monitor and deploy.

Measurement 246

Measurement Metrics Data-driven Testing 246

Smarten

AUGUST 4, 2023

Look for a solution with no requirement for SQL skills or the need for manual skills in data extraction, transformation, and loading (ETL). An augmented analytics solution that leverages machine learning can provide recommendations for users, so that they achieve the results they need, quickly and easily.

Data Lake 52

Data Lake Machine Learning Data Integration Optimization 52

CIO Business Intelligence

NOVEMBER 7, 2023

Given the importance of sharing information among diverse disciplines in the era of digital transformation, this concept is arguably as important as ever. The aim is to normalize, aggregate, and eventually make available to analysts across the organization data that originates in various pockets of the enterprise.

Data Warehouse 140

Data Warehouse Digital Transformation Data-driven Reporting 140

Rocket-Powered Data Science

MARCH 20, 2023

We live in a data-rich, insights-rich, and content-rich world. Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science. Source: [link] I will finish with three quotes.

Data Warehouse 325

Data Warehouse Metadata Digital Transformation Unstructured Data 325

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

AWS Big Data

APRIL 5, 2023

Showpad built new customer-facing embedded dashboards within Showpad eOSTM and migrated its legacy dashboards to Amazon QuickSight , a unified BI service providing modern interactive dashboards, natural language querying, paginated reports, machine learning (ML) insights, and embedded analytics at scale.

Dashboards 52

Dashboards Reporting Cost-Benefit Visualization 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. What is an ETL pipeline?

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

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