CIO Business Intelligence

NOVEMBER 27, 2024

Once the province of the data warehouse team, data management has increasingly become a C-suite priority, with data quality seen as key for both customer experience and business performance. But along with siloed data and compliance concerns , poor data quality is holding back enterprise AI projects.

Enterprise 141

Enterprise Data Quality Structured Data Modeling 141

Octopai

APRIL 8, 2019

There are two primary reasons for this: Manual data discovery and manual data lineage. Money Loser #1: Manual Data Discovery. Metadata is at the heart of every report, dashboard, data warehouse, visualization, and anything else the BI team produces. Money Loser #2: Manual Data Lineage.

Metadata 65

Metadata Dashboards Data Warehouse Visualization 65

AWS Big Data

FEBRUARY 26, 2025

Amazon SageMaker Lakehouse provides an open data architecture that reduces data silos and unifies data across Amazon Simple Storage Service (Amazon S3) data lakes, Redshift data warehouses, and third-party and federated data sources. With AWS Glue 5.0, AWS Glue 5.0 Finally, AWS Glue 5.0

Analytics 59

Analytics Data Lake Metadata Data Warehouse 59

Sisense

SEPTEMBER 3, 2019

This blog is intended to give an overview of the considerations you’ll want to make as you build your Redshift data warehouse to ensure you are getting the optimal performance. Think of it like something that houses the metrics used to power daily, weekly, or monthly business KPIs. roll-ups of many rows of data).

Data Warehouse 78

Data Warehouse OLAP Statistics Cost-Benefit 78

DataKitchen

SEPTEMBER 21, 2023

Data in Place refers to the organized structuring and storage of data within a specific storage medium, be it a database, bucket store, files, or other storage platforms. In the contemporary data landscape, data teams commonly utilize data warehouses or lakes to arrange their data into L1, L2, and L3 layers.

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

DataKitchen

JUNE 24, 2021

Previously we would have a very laborious data warehouse or data mart initiative and it may take a very long time and have a large price tag. GE formed its Digital League to create a data culture. Chapin also mentioned that measuring cycle time and benchmarking metrics upfront was absolutely critical. “It

Metrics 211

Metrics ROI Measurement Cost-Benefit 211

Alation

OCTOBER 18, 2022

Alation is pleased to be named a dbt Metrics Partner and to announce the start of a partnership with dbt, which will bring dbt data into the Alation data catalog. In the modern data stack, dbt is a key tool to make data ready for analysis. Data Transformation in the Modern Data Stack.

Metadata 52

Metadata Metrics Recreation/Entertainment Data Quality 52

AWS Big Data

JUNE 10, 2024

Since Apache Iceberg is well supported by AWS data services and Cloudinary was already using Spark on Amazon EMR, they could integrate writing to Data Catalog and start an additional Spark cluster to handle data maintenance and compaction. Each change to a table produces a new metadata file to provide atomicity.

Data Lake 121

Data Lake Metadata Snapshot Analytics 121

AWS Big Data

NOVEMBER 29, 2023

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

Data Lake 116

Data Lake Management Metrics Data Warehouse 116

AWS Big Data

DECEMBER 4, 2024

With this new functionality, customers can create up-to-date replicas of their data from applications such as Salesforce, ServiceNow, and Zendesk in an Amazon SageMaker Lakehouse and Amazon Redshift. SageMaker Lakehouse gives you the flexibility to access and query your data in-place with all Apache Iceberg compatible tools and engines.

Data Integration 97

Data Integration Data Lake Statistics Data-driven 97

CIO Business Intelligence

DECEMBER 21, 2022

Stout, for instance, explains how Schellman addresses integrating its customer relationship management (CRM) and financial data. “A A lot of business intelligence software pulls from a data warehouse where you load all the data tables that are the back end of the different software,” she says. “Or

IT 131

IT Business Intelligence Sales Key Performance Indicator 131

CIO Business Intelligence

NOVEMBER 22, 2022

External data sharing gets strategic Data sharing between business partners is becoming far easier and much more cooperative, observes Mike Bechtel, chief futurist at business advisory firm Deloitte Consulting. The fabric, especially at the active metadata level, is important, Saibene notes.

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

AWS Big Data

MARCH 5, 2025

Data sharing has become a crucial aspect of driving innovation, contributing to growth, and fostering collaboration across industries. According to this Gartner study , organizations promoting data sharing outperform their peers on most business value metrics. You will then publish the data assets from these data sources.

Analytics 59

Analytics Publishing Metadata Sales 59

AWS Big Data

SEPTEMBER 11, 2024

The application supports custom workflows to allow demand and supply planning teams to collaborate, plan, source, and fulfill customer orders, then track fulfillment metrics via persona-based operational and management reports and dashboards. This metadata file is later used to read source file names during processing into the staging layer.

Data Architecture 96

Data Architecture Optimization Data Warehouse Metadata 96

AWS Big Data

FEBRUARY 29, 2024

First, many LLM use cases rely on enterprise knowledge that needs to be drawn from unstructured data such as documents, transcripts, and images, in addition to structured data from data warehouses. Data enrichment In addition, additional metadata may need to be extracted from the objects.

Data Governance 109

Data Governance Unstructured Data Metadata Data Lake 109

AWS Big Data

AUGUST 15, 2024

To learn more, see Amazon DataZone now integrates with AWS Glue Data Quality and external data quality solutions. In this post, we show how to capture the data quality metrics for data assets produced in Amazon Redshift. For instructions, refer to Amazon DataZone quickstart with Amazon Redshift data.

Data Quality 106

Data Quality Visualization Metadata Key Performance Indicator 106

AWS Big Data

JULY 27, 2023

Amazon Redshift is a fully managed, scalable cloud data warehouse that accelerates your time to insights with fast, easy, and secure analytics at scale. Tens of thousands of customers rely on Amazon Redshift to analyze exabytes of data and run complex analytical queries, making it the widely used cloud data warehouse.

Data Warehouse 90

Data Warehouse Analytics Metadata Dashboards 90

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 96

Enterprise Data Warehouse Snapshot Cost-Benefit 96

AWS Big Data

MARCH 7, 2023

Data lakes are more focused around storing and maintaining all the data in an organization in one place. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.

Analytics 78

Analytics Data Warehouse Data Lake Metadata 78

AWS Big Data

OCTOBER 9, 2024

Today, customers are embarking on data modernization programs by migrating on-premises data warehouses and data lakes to the AWS Cloud to take advantage of the scale and advanced analytical capabilities of the cloud. In addition, you can select Add new columns to indicate data quality errors.

Data Quality 95

Data Quality Data Lake Data Warehouse Metrics 95

AWS Big Data

DECEMBER 4, 2024

In today’s data-driven world , organizations are constantly seeking efficient ways to process and analyze vast amounts of information across data lakes and warehouses. SageMaker Lakehouse gives you the flexibility to access and query your data in-place with all Apache Iceberg compatible tools and engines. S3FileIO').config('spark.hadoop.fs.s3a.aws.credentials.provider','org.apache.hadoop.fs.s3a.SimpleAWSCredentialProvider').config('spark.sql.catalog.spark_catalog.rest

Data Lake 106

Data Lake Metadata Insurance Data-driven 106

AWS Big Data

NOVEMBER 15, 2023

It seamlessly consolidates data from various data sources within AWS, including AWS Cost Explorer (and forecasting with Cost Explorer ), AWS Trusted Advisor , and AWS Compute Optimizer. Data providers and consumers are the two fundamental users of a CDH dataset.

Dashboards 106

Dashboards Analytics Metadata Data Warehouse 106

Alation

MAY 24, 2022

generally available on May 24, Alation introduces the Open Data Quality Initiative for the modern data stack, giving customers the freedom to choose the data quality vendor that’s best for them with the added confidence that those tools will integrate seamlessly with Alation’s Data Catalog and Data Governance application.

Data Quality 98

Data Quality Data Governance Metadata Metrics 98

AWS Big Data

DECEMBER 21, 2023

To speed up the self-service analytics and foster innovation based on data, a solution was needed to provide ways to allow any team to create data products on their own in a decentralized manner. To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse.

Data Lake 103

Data Lake Data Warehouse Data-driven B2B 103

Octopai

NOVEMBER 13, 2022

If you want to know why a report from Power BI delivered a particular number, data lineage traces that data point back through your data warehouse or lakehouse, back through your data integration tool, back to where the data basis for that report metric first entered your system.

Enterprise 97

Enterprise Data Warehouse Reporting Metadata 97

erwin

MARCH 8, 2019

Therefore, the organization needed to catalog the data it acquires from suppliers, ensure its quality, classify it, and then sell it to customers. The company wanted to assemble the data in a data warehouse and then provide controlled access to it.

Data Governance 65

Data Governance Metadata Data Warehouse Data Quality 65

AWS Big Data

MARCH 7, 2024

At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. With this massive data growth, data proliferation across your data stores, data warehouse, and data lakes can become equally challenging.

Data Lake 124

Data Lake Analytics Dashboards Metrics 124

AWS Big Data

JANUARY 24, 2023

This solution only replicates metadata in the Data Catalog, not the actual underlying data. To have a redundant data lake using Lake Formation and AWS Glue in an additional Region, we recommend replicating the Amazon S3-based storage using S3 replication , S3 sync, aws-s3-copy-sync-using-batch or S3 Batch replication process.

Data Architecture 72

Data Architecture Metadata Data Lake Snapshot 72

AWS Big Data

FEBRUARY 21, 2023

Data warehouses play a vital role in healthcare decision-making and serve as a repository of historical data. A healthcare data warehouse can be a single source of truth for clinical quality control systems. What is a dimensional data model? What is a dimensional data model? What is a data vault?

Data Warehouse 70

Data Warehouse Data Lake Cost-Benefit Metadata 70

Jet Global

JULY 2, 2019

The sheer scale of data being captured by the modern enterprise has necessitated a monumental shift in how that data is stored. From the humble database through to data warehouses , data stores have grown both in scale and complexity to keep pace with the businesses they serve, and the data analysis now required to remain competitive.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

AWS Big Data

MARCH 26, 2024

The following figure shows some of the metrics derived from the study. Profile aggregation – When you’ve uniquely identified a customer, you can build applications in Managed Service for Apache Flink to consolidate all their metadata, from name to interaction history. Then, you transform this data into a concise format.

Data Strategy 78

Data Strategy Strategy Data Warehouse Prescriptive Analytics 78

AWS Big Data

SEPTEMBER 13, 2023

The Analytics specialty practice of AWS Professional Services (AWS ProServe) helps customers across the globe with modern data architecture implementations on the AWS Cloud. The File Manager Lambda function consumes those messages, parses the metadata, and inserts the metadata to the DynamoDB table odpf_file_tracker.

Data Lake 103

Data Lake Data Processing Metadata Snapshot 103

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale. Frequent table maintenance needs to be performed to prevent read performance from degrading over time.

Data Lake 125

Data Lake Metadata Statistics Optimization 125

Alation

AUGUST 26, 2021

What Is Data Intelligence? Data intelligence is a system to deliver trustworthy, reliable data. It includes intelligence about data, or metadata. IDC coined the term, stating, “data intelligence helps organizations answer six fundamental questions about data.” Yet finding data is just the beginning.

Metadata 64

Metadata Data Governance Dashboards Software 64

Sisense

JANUARY 6, 2020

Analysts can use SQL as a more powerful tool than Salesforce to model messy sales data. By applying complex logic, you can more seamlessly build data models and gain fast, more advanced analysis. To achieve this, first requires getting the data into a form that delivers insights. Calculate opportunity metadata 5.

Sales 91

Sales Forecasting Snapshot Management 91

Ontotext

OCTOBER 14, 2021

For the purposes of this article, you just need to know the following: A graph is a method of storing and modeling data that uniquely captures the relationships between data. A knowledge graph uses this format to integrate data from different sources while enriching it with metadata that documents collective knowledge about the data.

Reporting 98

Reporting Structured Data Data Warehouse Metadata 98

Octopai

JUNE 1, 2020

Implementing good data mapping practices is an important way modern enterprise organizations use advanced business metrics for strategic insight. With the rapid rise of new data regulations across the globe, capable data mapping isn’t just a tool for companies to get a leg up on the competition – it is required for legal compliance.

Metadata 52

Metadata Data Warehouse Data Integration Finance 52