Cloudera

AUGUST 17, 2021

When we announced the GA of Cloudera Data Engineering back in September of last year, a key vision we had was to simplify the automation of data transformation pipelines at scale. Typically users need to ingest data, transform it into optimal format with quality checks, and optimize querying of the data by visual analytics tool.

Management 115

Management Cost-Benefit Data Transformation Optimization 115

AWS Big Data

JANUARY 30, 2025

AWS Step Functions With AWS Step Functions, you can create workflows, also called State machines, to build distributed applications, automate processes, orchestrate microservices, and create data and machine learning pipelines. The following Diagram 2 shows this workflow. The following Diagram 4 shows this workflow.

Data Warehouse 54

Data Warehouse Data Architecture Machine Learning Data Transformation 54

AWS Big Data

OCTOBER 11, 2023

Under the Transparency in Coverage (TCR) rule , hospitals and payors to publish their pricing data in a machine-readable format. 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.

Visualization 119

Visualization Dashboards Data-driven Gap analysis 119

erwin

MARCH 26, 2020

There are three technological advances driving this data consumption and, in turn, the ability for employees to leverage this data to deliver business value 1) exploding data production 2) scalable big data computation, and 3) the accessibility of advanced analytics, machine learning (ML) and artificial intelligence (AI).

Data-driven 90

Data-driven Unstructured Data Enterprise Machine Learning 90

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 104

Testing Big Data Metadata Optimization 104

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. Finally, click “Publish” in the upper right hand corner, and you’re ready to create a dashboard! This is where we’ll create a new dashboard to view and explore the data.

Dashboards 98

Dashboards IoT Optimization Internet of Things 98

AWS Big Data

FEBRUARY 6, 2023

The most common use case for Airflow is ETL (extract, transform, and load). Operationalizing machine learning (ML) is another growing use case, where data has to be transformed and normalized before it can be loaded into an ML model. format(S3_BUCKET_NAME), 's3://{}/data/aggregated/green'.format(S3_BUCKET_NAME),

Management 98

Management Interactive Publishing Metadata 98

IBM Big Data Hub

JULY 17, 2023

is our enterprise-ready next-generation studio for AI builders, bringing together traditional machine learning (ML) and new generative AI capabilities powered by foundation models. Automated development: Automates data preparation, model development, feature engineering and hyperparameter optimization using AutoAI.

Machine Learning 62

Machine Learning Data Warehouse Modeling Cost-Benefit 62

AWS Big Data

APRIL 25, 2023

The following AWS services are used for data ingestion, processing, and load: Amazon AppFlow is a fully managed integration service that enables you to securely transfer data between SaaS applications like Salesforce, SAP, Marketo, Slack, and ServiceNow, and AWS services like Amazon S3 and Amazon Redshift , in just a few clicks.

Sales 97

Sales Visualization Software Metadata 97

AWS Big Data

AUGUST 1, 2024

Migrating to Amazon Redshift offers organizations the potential for improved price-performance, enhanced data processing, faster query response times, and better integration with technologies such as machine learning (ML) and artificial intelligence (AI). Platform architects define a well-architected platform.

Data Warehouse 115

Data Warehouse KPI Optimization Cost-Benefit 115

IBM Big Data Hub

JANUARY 18, 2023

They defined it as : “ A data lakehouse is a new, open data management architecture that combines the flexibility, cost-efficiency, and scale of data lakes with the data management and ACID transactions of data warehouses, enabling business intelligence (BI) and machine learning (ML) on all data. ”.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

AWS Big Data

JULY 26, 2023

At the time of publishing of this post, the AWS CDK has two versions of the AWS Glue module: @aws-cdk/aws-glue and @aws-cdk/aws-glue-alpha , containing L1 constructs and L2 constructs , respectively. Then you will see a view similar to the following screenshot.

Data Integration 97

Data Integration Snapshot Testing Visualization 97

Alation

NOVEMBER 22, 2022

With data governance, public sector entities can publish data ethically, using open-data portals and giving citizens visibility into how their data is used. Modernizes Data Systems. Data governance enables structured and secure data exchanges for systems built on the premise of privacy-by-design.

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 Visualization 52

Jet Global

MAY 1, 2023

Strategic Objective Create a complete, user-friendly view of the data by preparing it for analysis. Requirement Multi-Source Data Blending Data from multiple sources is compiled and the output is a single view, metric, or visualization. Data Transformation and Enrichment Data can be enriched for analysis.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

AWS Big Data

NOVEMBER 6, 2024

Iceberg brings the reliability and simplicity of SQL tables to Amazon Simple Storage Service (Amazon S3) data lakes. In our examples, we use Kinesis Data Generator , a sample application to generate and publish data streams to Firehose. You can also set up Firehose to use other data sources for your real-time streams.

Metadata 116

Metadata Data Lake Management Internet of Things 116