Alation

JUNE 28, 2022

Scale effectively: Leverage taxonomies to ensure consistent modeling outcomes when introducing new data sets or changing business demands. Track data lineage: Document data origins, record data transformation and movement, and visualize flow throughout the entire data lifecycle. Supports Strong Data Culture.

Metadata 52

Metadata Management Data Governance Machine Learning 52

Sisense

AUGUST 6, 2020

AI and machine learning (ML) are not just catchy buzzwords; they’re vital to the future of our planet and your business. Doing it right can mean the difference between thriving in the new world of data and disappearing from it. What data transformations are needed from your data scientists to prepare the data?

Management 95

Management Machine Learning Key Performance Indicator Cost-Benefit 95

AWS Big Data

OCTOBER 11, 2023

The data in the machine-readable files can provide valuable insights to understand the true cost of healthcare services and compare prices and quality across hospitals. The availability of machine-readable files opens up new possibilities for data analytics, allowing organizations to analyze large amounts of pricing data.

Visualization 97

Visualization Dashboards Data-driven Gap analysis 97

IBM Big Data Hub

MARCH 14, 2024

For existing IBM on-premises database customers, transitioning to AWS is seamless, offering risk-free, like-for-like upgrades.  Netezza incorporates in-database analytics and machine learning (ML), governance, security and patented massively parallel processing.

Cost-Benefit 76

Cost-Benefit Metadata Optimization Management 76

AWS Big Data

APRIL 12, 2023

Also, you can run other types of business applications, such as web applications and machine learning (ML) TensorFlow workloads, on the same EKS cluster. We have been continually improving the Spark performance in each Amazon EMR release to further shorten job runtime and optimize users’ spending on their Amazon EMR big data workloads.

Testing 76

Testing Big Data Metadata Optimization 76

AWS Big Data

FEBRUARY 21, 2023

We use Apache Spark as our main data processing engine and have over 1,000 Spark applications running over massive amounts of data every day. These Spark applications implement our business logic ranging from data transformation, machine learning (ML) model inference, to operational tasks.

Cost-Benefit 55

Cost-Benefit Informatics Optimization Management 55

AWS Big Data

JULY 25, 2023

Redshift Serverless automatically provisions and intelligently scales data warehouse capacity to deliver fast performance for even the most demanding and unpredictable workloads, and you pay only for what you use. For Username and Password , enter your user name and password, respectively.

Data Analytics 52

Data Analytics Data Warehouse Analytics Data Processing 52

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

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

CIO Business Intelligence

JUNE 14, 2022

For years, IT and data leaders have been striving to help their companies become more data driven. But technology investment alone is not enough to make your organization data driven. I think that speaks volumes to the type of commitment that organizations have to make around data in order to actually move the needle.”.

Data Transformation 145

Data Transformation Data-driven Data Strategy Strategy 145

bridgei2i

SEPTEMBER 3, 2020

Ronobijay: Sure, I think it would, you know, what used to be anathema till a few months back, you know, data transformation is real now, right? One of the most impactful areas for AI-led intelligent operations is machine learning-based analytics applied towards increasing their operational efficiencies. Arjun: Absolutely.

Enterprise 94

Enterprise Insurance Digital Transformation Interactive 94

AWS Big Data

SEPTEMBER 19, 2023

Chime’s Risk Analysis team constantly monitors trends in our data to find patterns that indicate fraudulent transactions. However, with a minimum data freshness of 10 minutes, this architecture inherently didn’t align with the near real-time fraud detection use case.

Analytics 79

Analytics Risk Big Data Machine Learning 79

CIO Business Intelligence

JANUARY 24, 2024

The Agent Swarm evolution has been propelled by advancements in computing, artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT). Use predefined rules, machine learning models, or a combination of both to make informed decisions.

IoT 113

IoT Machine Learning Optimization Internet of Things 113

Alation

NOVEMBER 22, 2022

When using a data governance tool, like a data catalog , entities can find deprecated or outdated data, which is not fit for wider consumption or analysis. With data governance, public sector entities mitigate fraud risk by aggregating data across registers to ensure consistency. Improve data visibility.

Data Governance 52

Data Governance Metadata Data-driven Unstructured Data 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

This field guide to data mapping will explore how data mapping connects volumes of data for enhanced decision-making. 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 Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Jet Global

MAY 1, 2023

CEO Priorities Grow revenue and “hit the number” Manage costs and meet profitability goals Attract and retain talent Innovate and out-perform the competition Manage risk Connect the Dots Present embedded analytics as a way to differentiate from the competition and increase revenue. Present your business case. addresses).

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52