Alation

APRIL 6, 2023

Data governance is traditionally applied to structured data assets that are most often found in databases and information systems. This blog focuses on governing spreadsheets that contain data, information, and metadata, and must themselves be governed.

Data Governance 52

Data Governance Metadata Cost-Benefit Structured Data 52

AWS Big Data

MARCH 7, 2023

Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. A data hub is a center of data exchange that constitutes a hub of data repositories and is supported by data engineering, data governance, security, and monitoring services.

Analytics 74

Analytics Data Warehouse Data Lake Metadata 74

AWS Big Data

MARCH 27, 2024

The solution uses AWS services such as AWS HealthLake , Amazon Redshift , Amazon Kinesis Data Streams , and AWS Lake Formation to build a 360 view of patients. You can send data from your streaming source to this resource for ingesting the data into a Redshift data warehouse. reference", SUBSTRING(a."patient"."reference",

Data Analytics 93

Data Analytics Analytics Data Warehouse Data Lake 93

AWS Big Data

SEPTEMBER 25, 2023

With Amazon Redshift , you can run a complex mix of workloads on your data warehouse, such as frequent data loads running alongside business-critical dashboard queries and complex transformation jobs. We also see more and more data science and machine learning (ML) workloads. ExampleCorp has multiple Redshift clusters.

Management 97

Management Data Warehouse Metrics Dashboards 97

AWS Big Data

JANUARY 31, 2023

Data governance is the collection of policies, processes, and systems that organizations use to ensure the quality and appropriate handling of their data throughout its lifecycle for the purpose of generating business value.

Data Lake 84

Data Lake Data Governance Data Architecture Machine Learning 84

AWS Big Data

JUNE 28, 2023

For more details, refer to the What’s New Post. There are two broad approaches to analyzing operational data for these use cases: Analyze the data in-place in the operational database (e.g. For this illustration, we use a provisioned Aurora database and an Amazon Redshift Serverless data warehouse.

Data Warehouse 87

Data Warehouse Analytics Metrics Dashboards 87

AWS Big Data

JULY 25, 2023

The integration of Talend Cloud and Talend Stitch with Amazon Redshift Serverless can help you achieve successful business outcomes without data warehouse infrastructure management. In this post, we demonstrate how Talend easily integrates with Redshift Serverless to help you accelerate and scale data analytics with trusted data.

Data Analytics 52

Data Analytics Data Warehouse Analytics Data Processing 52

IBM Big Data Hub

JANUARY 17, 2023

A data lakehouse is an emerging data management architecture that improves efficiency and converges data warehouse and data lake capabilities driven by a need to improve efficiency and obtain critical insights faster. Let’s start with why data lakehouses are becoming increasingly important.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

AWS Big Data

MAY 7, 2024

Data governance is a key enabler for teams adopting a data-driven culture and operational model to drive innovation with data. Amazon DataZone allows you to simply and securely govern end-to-end data assets stored in your Amazon Redshift data warehouses or data lakes cataloged with the AWS Glue data catalog.

Metadata 77

Metadata Data Lake Data Processing Data-driven 77

AWS Big Data

MARCH 26, 2024

In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges. This consolidated view acts as a liaison between the data platform and customer-centric applications.

Data Strategy 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

AWS Big Data

DECEMBER 19, 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 a widely used cloud data warehouse.

Data Analytics 62

Data Analytics Analytics Data Warehouse Data-driven 62

erwin

FEBRUARY 28, 2019

When you think of real-time, data-driven experiences and modern applications to accomplish tasks faster and easier, your local town or city government probably doesn’t come to mind. But municipal government is starting to embrace digital transformation and therefore data governance.

Digital Transformation 106

Digital Transformation Data Governance Data-driven Data Warehouse 106

CIO Business Intelligence

MARCH 22, 2022

One option is a data lake—on-premises or in the cloud—that stores unprocessed data in any type of format, structured or unstructured, and can be queried in aggregate. Another option is a data warehouse, which stores processed and refined data. Set up unified data governance rules and processes.

Analytics 103

Analytics Key Performance Indicator Data Warehouse Data-driven 103

erwin

FEBRUARY 7, 2019

Organization’s cannot hope to make the most out of a data-driven strategy, without at least some degree of metadata-driven automation. The volume and variety of data has snowballed, and so has its velocity. As such, traditional – and mostly manual – processes associated with data management and data governance have broken down.

Metadata 96

Metadata Insurance Data-driven Cost-Benefit 96

AWS Big Data

JULY 21, 2023

This leads to having data across many instances of data warehouses and data lakes using a modern data architecture in separate AWS accounts. We recently announced the integration of Amazon Redshift data sharing with AWS Lake Formation. S3 data lake – Contains the web activity and leads datasets.

Data Lake 89

Data Lake Data Warehouse Marketing Management 89

AWS Big Data

JULY 28, 2023

Amazon Redshift is a petabyte-scale, enterprise-grade cloud data warehouse service delivering the best price-performance. Today, tens of thousands of customers run business-critical workloads on Amazon Redshift to cost-effectively and quickly analyze their data using standard SQL and existing business intelligence (BI) tools.

Data Lake 69

Data Lake Data Governance Data Warehouse Modeling 69

erwin

JULY 17, 2019

The solution is data intelligence. It improves IT and business data literacy and knowledge, supporting enterprise data governance and business enablement. Organizations need a real-time, accurate picture of the metadata landscape to: Discover data – Identify and interrogate metadata from various data management silos.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

Alation

MAY 16, 2023

Data classification, standardization, normalization, verification, validation, and deduplication are all examples of data processing tasks. Data Storage The data storage component of a pipeline provides secure, scalable storage for the data. You also want to make sure that there aren’t any issues with the data.

Data Lake 69

Data Lake Data Governance Data Warehouse Data Processing 69

AWS Big Data

APRIL 25, 2024

Amazon Managed Workflows for Apache Airflow (Amazon MWAA) is a managed orchestration service for Apache Airflow that you can use to set up and operate data pipelines in the cloud at scale. Apache Airflow is an open source tool used to programmatically author, schedule, and monitor sequences of processes and tasks, referred to as workflows.

Metadata 106

Metadata Data Processing Management Testing 106

IBM Big Data Hub

AUGUST 4, 2023

In turn, they both must also have the data literacy skills to be able to verify the data’s accuracy, ensure its security, and provide or follow guidance on when and how it should be used. By recognizing data as a product, it creates greater incentive to properly manage data.

Data Architecture 62

Data Architecture Data Lake Machine Learning Data Governance 62

CIO Business Intelligence

OCTOBER 13, 2022

The deliverables could be reference architectures or an industry-specific proof of concept—the goal is to offer institutional knowledge and near-turn-key solutions meant to streamline modernization and accelerate time-to-value.

Insurance 101

Insurance Data Warehouse Manufacturing Forecasting 101

erwin

JULY 2, 2020

a senior business process management architect at a pharma/biotech company with more than 5,000 employees, erwin Evolve was useful for enterprise architecture reference. As he put it, “We are describing our business process and we are trying to describe our data catalog. Data Modeling with erwin Data Modeler. George H.,

Enterprise 122

Enterprise Modeling Metadata Data Governance 122

AWS Big Data

JULY 28, 2023

Organizations must comply with these requests provided that there are no legitimate grounds for retaining the personal data, such as legal obligations or contractual requirements. Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Tags provide metadata about resources at a glance.

Snapshot 86

Snapshot Metadata Measurement Data Warehouse 86

Alation

JANUARY 17, 2023

The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform. It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

BizAcuity

APRIL 1, 2023

Thanks to the recent technological innovations and circumstances to their rapid adoption, having a data warehouse has become quite common in various enterprises across sectors. Data governance and security measures are critical components of data strategy.

Business Intelligence 52

Business Intelligence Consulting KPI Data Warehouse 52

AWS Big Data

OCTOBER 20, 2023

Prerequisites You need the following prerequisites: A storage account in Microsoft Azure and your data path in Azure Blob Storage. For instructions, refer to Create a storage account shared key. For instructions, refer to Creating ETL jobs with AWS Glue Studio. Prepare the storage account credentials in advance.

Data Lake 86

Data Lake Big Data Consulting Data Warehouse 86

BizAcuity

JANUARY 31, 2023

Thanks to the recent technological innovations and circumstances to their rapid adoption, having a data warehouse has become quite common in various enterprises across sectors. Data governance and security measures are critical components of data strategy.

Business Intelligence 52

Business Intelligence Consulting KPI Data Warehouse 52

AWS Big Data

FEBRUARY 19, 2024

Amazon Redshift is a fast, petabyte-scale, cloud data warehouse that tens of thousands of customers rely on to power their analytics workloads. Thousands of customers use Amazon Redshift read data sharing to enable instant, granular, and fast data access across Redshift provisioned clusters and serverless workgroups.

Cost-Benefit 87

Cost-Benefit Data Warehouse Marketing Interactive 87

Cloudera

AUGUST 26, 2020

Talend’s data management environment running on Cloudera Data Platform enables you to create and execute Hadoop and Spark integration jobs, process and reconcile Big Data, and implement data governance processes using an intuitive drag-and-drop interface. Reference Architectures for CDP Private Cloud Base.

Machine Learning 82

Machine Learning Big Data Data Warehouse Data-driven 82

Alation

FEBRUARY 13, 2020

Data curation is important in today’s world of data sharing and self-service analytics, but I think it is a frequently misused term. When speaking and consulting, I often hear people refer to data in their data lakes and data warehouses as curated data, believing that it is curated because it is stored as shareable data.

Metadata 52

Metadata Data Warehouse Data Lake Data Governance 52

datapine

SEPTEMBER 29, 2022

Reporting being part of an effective DQM, we will also go through some data quality metrics examples you can use to assess your efforts in the matter. But first, let’s define what data quality actually is. What is the definition of data quality? Why Do You Need Data Quality Management?

Data Quality 241

Data Quality Metrics Data-driven Management 241

Laminar Security

DECEMBER 13, 2023

They offer a comprehensive solution to enhance your cloud security posture and effectively manage your data. The primary focus of discovery is to find all the places where data exists and identify the assets it resides in. It helps in determining what data you have and its sensitivity.

Data-driven 119

Data-driven Machine Learning Risk Deep Learning 119

AWS Big Data

JULY 19, 2023

Amazon Redshift is a fully managed and petabyte-scale cloud data warehouse that is used by tens of thousands of customers to process exabytes of data every day to power their analytics workload. You can structure your data, measure business processes, and get valuable insights quickly can be done by using a dimensional model.

Modeling 71

Modeling Sales Data Warehouse Snapshot 71

AWS Big Data

JULY 13, 2023

Data quality for account and customer data – Altron wanted to enable data quality and data governance best practices. Goals – Lay the foundation for a data platform that can be used in the future by internal and external stakeholders. Basic formatting and readability of the data is standardized here.

Optimization 92

Optimization B2B Data Quality Sales 92

erwin

JUNE 26, 2020

It’s no surprise that most organizations’ data is often fragmented and siloed across numerous sources (e.g., legacy systems, data warehouses, flat files stored on individual desktops and laptops, and modern, cloud-based repositories.). Business Metadata.

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

Alation

DECEMBER 21, 2022

MDM is a discipline that helps organize critical information to avoid duplication, inconsistency, and other data quality issues. Transactional systems and data warehouses can then use the golden records as the entity’s most current, trusted representation. Data Catalog and Master Data Management.

Management 52

Management Data Quality Metadata Testing 52

Jet Global

FEBRUARY 23, 2024

ETL is beneficial for larger data volumes and diverse sources, and may be necessary for data architects, developers, and administrators considering factors like volume, source diversity, accuracy, and efficiency. Data Migration Data migration refers to the process of transferring data from one location or format to another.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52