Cloudera

OCTOBER 11, 2021

Modak Nabu reliably curates datasets for any line of business and personas, from business analysts to data scientists. Customers using Modak Nabu with CDP today have deployed Data Lakes and. An executive dashboard shows the status of crawlers, pipelines, and data profiling.

Data Lake 92

Data Lake Cost-Benefit Data-driven Dashboards 92

IBM Big Data Hub

JUNE 15, 2023

It is comprised of commodity cloud object storage, open data and open table formats, and high-performance open-source query engines. To help organizations scale AI workloads, we recently announced IBM watsonx.data , a data store built on an open data lakehouse architecture and part of the watsonx AI and data platform.

Data Warehouse 88

Data Warehouse Data Lake Optimization Data-driven 88

AWS Big Data

FEBRUARY 6, 2023

Refactoring coupled compute and storage to a decoupling architecture is a modern data solution. It enables compute such as EMR instances and storage such as Amazon Simple Storage Service (Amazon S3) data lakes to scale. The QuickSight timeline dashboard shows the peak time job runs because of the daily batch job.

Cost-Benefit 52

Cost-Benefit Data Lake Dashboards Big Data 52

AWS Big Data

MARCH 3, 2023

Building data lakes from continuously changing transactional data of databases and keeping data lakes up to date is a complex task and can be an operational challenge. You can then apply transformations and store data in Delta format for managing inserts, updates, and deletes.

Data Lake 86

Data Lake Dashboards Metrics Metadata 86

AWS Big Data

FEBRUARY 6, 2023

Amazon QuickSight dashboards showcase the results from the analyzer. With QuickSight, you can visualize YARN log data and conduct analysis against the datasets generated by pre-built dashboard templates and a widget. This step creates datasets on QuickSight dashboards in your AWS target account.

Dashboards 78

Dashboards Optimization Data Lake Cost-Benefit 78

AWS Big Data

NOVEMBER 9, 2023

In this post, we delve into a case study for a retail use case, exploring how the Data Build Tool (dbt) was used effectively within an AWS environment to build a high-performing, efficient, and modern data platform. It does this by helping teams handle the T in ETL (extract, transform, and load) processes.

Data Warehouse 107

Data Warehouse Testing Data Quality Reporting 107

AWS Big Data

MARCH 3, 2023

Initially, Tricentis defines these dashboards and charts to enable insight on test runs, test traceability with requirements, and many other pre-defined use cases that can be valuable to customers. As the files are created, another process is triggered to load the data from each customer on their schema or table on Amazon Redshift.

Software 52

Software Data Lake Testing Cost-Benefit 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

IBM Big Data Hub

OCTOBER 16, 2023

How to scale AL and ML with built-in governance A fit-for-purpose data store built on an open lakehouse architecture allows you to scale AI and ML while providing built-in governance tools. A data store lets a business connect existing data with new data and discover new insights with real-time analytics and business intelligence.

Risk 72

Risk Modeling Management Metadata 72

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 87

Enterprise Data Warehouse Data Lake Optimization 87

O'Reilly on Data

OCTOBER 19, 2021

If you ask an engineer to show how they operate the application in production, they will likely show containers and operational dashboards—not unlike any other software service. ML use cases rarely dictate the master data management solution, so the ML stack needs to integrate with existing data warehouses. Model Development.

IT 342

IT Testing Experimentation Software 342

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

AWS Big Data

JUNE 29, 2023

In our solution, we create a notebook to access automotive sensor data, enrich the data, and send the enriched output from the Kinesis Data Analytics Studio notebook to an Amazon Kinesis Data Firehose delivery stream for delivery to an Amazon Simple Storage Service (Amazon S3) data lake.

Data Analytics 76

Data Analytics Analytics IoT Data Lake 76

AWS Big Data

MAY 25, 2023

Data transformation plays a pivotal role in providing the necessary data insights for businesses in any organization, small and large. To gain these insights, customers often perform ETL (extract, transform, and load) jobs from their source systems and output an enriched dataset.

Reporting 72

Reporting Metrics Optimization Data Lake 72

Sisense

MAY 11, 2021

The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. According to a recent survey conducted by IDC , 43% of respondents were drawing intelligence from 10 to 30 data sources in 2020, with a jump to 64% in 2021!

Modeling 84

Modeling Big Data IoT Data Warehouse 84