AWS Big Data

NOVEMBER 9, 2023

It does this by helping teams handle the T in ETL (extract, transform, and load) processes. It allows users to write data transformation code, run it, and test the output, all within the framework it provides. As part of their cloud modernization initiative, they sought to migrate and modernize their legacy data platform.

Data Warehouse 101

Data Warehouse Testing Data Quality Reporting 101

CIO Business Intelligence

JANUARY 24, 2024

“Organizations often get services and applications up and running without having put stewardship in place,” says Marc Johnson, CISO and senior advisor at Impact Advisors, a healthcare management consulting firm. Creating data silos Denying business users access to information because of data silos has been a problem for years.

Data Strategy 135

Data Strategy Strategy Unstructured Data Data Governance 135

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. So questions linger about whether transformed data can be trusted.

Data Governance 40

Data Governance Risk Metadata Management 40

CIO Business Intelligence

FEBRUARY 16, 2023

My vision is that I can give the keys to my businesses to manage their data and run their data on their own, as opposed to the Data & Tech team being at the center and helping them out,” says Iyengar, director of Data & Tech at Straumann Group North America. The offensive side?

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 105

IBM Big Data Hub

FEBRUARY 9, 2023

In our last blog , we delved into the seven most prevalent data challenges that can be addressed with effective data governance. Today we will share our approach to developing a data governance program to drive data transformation and fuel a data-driven culture.

Data Governance 80

Data Governance Business Objectives Strategy Data Quality 80

erwin

APRIL 29, 2020

Compliance with these business rules can be tracked through data lineage, incorporating auditability and validation controls across data transformations and pipelines to generate alerts when there are non-compliant data instances. Seeing data pipelines and information flows further supports compliance efforts.

Metadata 111

Metadata Data Governance Key Performance Indicator Data Quality 111

AWS Big Data

DECEMBER 21, 2023

AWS Glue provides both visual and code-based interfaces to make data integration effortless. Using a native AWS Glue connector increases agility, simplifies data movement, and improves data quality. Attach the AWS managed policy GlueServiceRole. Choose Dashboards Management on the navigation menu.

Analytics 93

Analytics IT Data Lake Visualization 93

Sisense

AUGUST 28, 2020

Uncomfortable truth incoming: Most people in your organization don’t think about the quality of their data from intake to production of insights. However, as a data team member, you know how important data integrity (and a whole host of other aspects of data management) is.

Data Integration 101

Data Integration Testing Data Quality Data-driven 101

DataKitchen

DECEMBER 9, 2022

DataOps involves close collaboration between data scientists, IT professionals, and business stakeholders, and it often involves the use of automation and other technologies to streamline data-related tasks. One of the key benefits of DataOps is the ability to accelerate the development and deployment of data-driven solutions.

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

Alation

MARCH 22, 2022

As the latest iteration in this pursuit of high-quality data sharing, DataOps combines a range of disciplines. It synthesizes all we’ve learned about agile, data quality , and ETL/ELT. In fact, DataOps places an outsized burden on data management teams. How the IDF Supports a Smarter Data Pipeline.

Metadata 52

Metadata Cost-Benefit Data Quality Data Lake 52

erwin

SEPTEMBER 17, 2020

Here are six benefits of automating end-to-end data lineage: Reduced Errors and Operational Costs. Data quality is crucial to every organization. Automated data capture can significantly reduce errors when compared to manual entry. Improved Customer and Employee Satisfaction.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

Sisense

OCTOBER 15, 2020

Dealing with this challenge requires caching the relevant context on the processing instances (state management) using techniques like sliding time windows. Another goal that teams dealing with streaming data may have is managing and optimizing a file system on object storage. Optimizing object storage. Ori has a B.A.

Dashboards 98

Dashboards IoT Optimization Internet of Things 98

AWS Big Data

APRIL 19, 2023

Data mesh is a new approach to data management. Companies across industries are using a data mesh to decentralize data management to improve data agility and get value from data. The goal of a data product is to solve the long-standing issue of data silos and data quality.

Technology 78

Technology Data-driven Machine Learning Sales 78

DataRobot Blog

MARCH 10, 2022

This is currently a widespread strategy across the industry where we are seeing companies move from reactive to predictive inventory management and capacity planning. These initiatives utilize interconnected devices and automated machines that create a hyperbolic increase in data volumes. Factory Monitoring?—?

Manufacturing 52

Manufacturing IoT Machine Learning Forecasting 52

Peter James Thomas

OCTOBER 30, 2018

Where they have, I have normally found the people holding these roles to be better informed about data matters than their peers. The same goes in general for Marketing Managers. It may well be that one thing that a CDO needs to get going is a data transformation programme. It may be to introduce or expand Data Governance.

Marketing 51

Marketing Strategy Data Architecture Data Strategy 51

CIO Business Intelligence

JUNE 23, 2022

Yet as companies fight for skilled analyst roles to utilize data to make better decisions , they often fall short in improving the data supply chain and resulting data quality. Without a solid data supply-chain management practices in place, data quality often suffers.

Data Quality 97

Data Quality Key Performance Indicator Metrics KPI 97

CIO Business Intelligence

DECEMBER 22, 2022

Research firm Gartner further describes the methodology as one focused on “improving the communication, integration, and automation of data flows between data managers and data consumers across an organization.” Data scientists may also be included as key members of DataOps teams, according to Dunning. “I

Analytics 129

Analytics Machine Learning Software Data Quality 129

Ontotext

MARCH 27, 2024

They also don’t have features for enterprise data management such as schema language, data validation capabilities, interoperable serialization formats, or a proper modeling language. RDF is used extensively for data publishing and data interchange and is based on W3C and other industry standards.

Modeling 69

Modeling Metadata Data Quality Enterprise 69

CIO Business Intelligence

DECEMBER 6, 2023

Despite logistics challenges caused by the global pandemic, the company managed to rapidly scale up its team to over 1,000 people in a period of only 11 months.

Digital Transformation 115

Digital Transformation Software Cost-Benefit Modeling 115

IBM Big Data Hub

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

Cost-Benefit 81

Cost-Benefit Metadata Optimization Management 81

erwin

MARCH 4, 2021

However, while digital transformation and other data-driven initiatives are desired outcomes, few organizations know what data they have or where it is, and they struggle to integrate known data in various formats and numerous systems – especially if they don’t have a way to automate those processes.

Data Governance 122

Data Governance Digital Transformation Data-driven Cost-Benefit 122

AWS Big Data

JULY 20, 2023

Prior to the creation of the data lake, Orca’s data was distributed among various data silos, each owned by a different team with its own data pipelines and technology stack. Moreover, running advanced analytics and ML on disparate data sources proved challenging.

Data Lake 84

Data Lake Analytics Snapshot Optimization 84

Alation

AUGUST 11, 2022

But there are only so many data engineers available in the market today; there’s a big skills shortage. So to get away from that lack of data engineers, what data mesh says is, ‘Take those business logic data transformation capabilities and move that to the domains.’ Let’s take data privacy as an example.

Metadata 52

Metadata Data Warehouse Data Quality Data Lake 52

AWS Big Data

FEBRUARY 8, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Amazon Redshift enables you to run complex SQL analytics at scale and performance on terabytes to petabytes of structured and unstructured data, and make the insights widely available through popular business intelligence (BI) and analytics tools.

Data Quality 73

Data Quality Testing Data Warehouse Unstructured Data 73

AWS Big Data

JULY 27, 2023

DataBrew is a visual data preparation tool that enables you to clean and normalize data without writing any code. The over 200 transformations it provides are now available to be used in an AWS Glue Studio visual job. Now that we identified the data quality issues to address, we need to decide how to deal with each case.

Visualization 79

Visualization Cost-Benefit Data Quality Interactive 79

Alation

OCTOBER 28, 2021

Leaders are asking how they might use data to drive smarter decision making to support this new model and improve medical treatments that lead to better outcomes. This data is also a lucrative target for cyber criminals. To make good on this potential, healthcare organizations need to understand their data and how they can use it.

Data Governance 52

Data Governance Measurement Modeling Metrics 52

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. About Octopai: Octopai was founded in 2015 by BI professionals who realized the need for dynamic solutions in a stagnant market.

Metadata 52

Metadata ROI Optimization Data Quality 52

AWS Big Data

MARCH 3, 2023

In this post, we share how the AWS Data Lab helped Tricentis to improve their software as a service (SaaS) Tricentis Analytics platform with insights powered by Amazon Redshift. Although Tricentis has amassed such data over a decade, the data remains untapped for valuable insights.

Software 52

Software Data Lake Testing Cost-Benefit 52

erwin

APRIL 16, 2024

The data mesh framework In the dynamic landscape of data management, the search for agility, scalability, and efficiency has led organizations to explore new, innovative approaches. One such innovation gaining traction is the data mesh framework. This empowers individual teams to own and manage their data.

Metadata 52

Metadata Data Quality Data Governance Modeling 52

DataKitchen

APRIL 26, 2021

In early April 2021, DataKItchen sat down with Jonathan Hodges, VP Data Management & Analytics, at Workiva ; Chuck Smith, VP of R&D Data Strategy at GlaxoSmithKline (GSK) ; and Chris Bergh, CEO and Head Chef at DataKitchen, to find out about their enterprise DataOps transformation journey, including key successes and lessons learned.

Measurement 246

Measurement Metrics Data-driven Testing 246

CIO Business Intelligence

NOVEMBER 7, 2023

Given the importance of sharing information among diverse disciplines in the era of digital transformation, this concept is arguably as important as ever. The aim is to normalize, aggregate, and eventually make available to analysts across the organization data that originates in various pockets of the enterprise.

Data Warehouse 141

Data Warehouse Digital Transformation Reporting Data-driven 141

Smart Data Collective

OCTOBER 13, 2021

There are countless examples of big data transforming many different industries. There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. How does Data Virtualization manage data quality requirements?

Visualization 135

Visualization Cost-Benefit Big Data Prescriptive Analytics 135

Rocket-Powered Data Science

MARCH 20, 2023

Datasphere accesses and integrates both SAP and non-SAP data sources into end-users’ data flows, including on-prem data warehouses, cloud data warehouses and lakehouses, relational databases, virtual data products, in-memory data, and applications that generate data (such as external API data loads).

Data Warehouse 324

Data Warehouse Metadata Digital Transformation Unstructured Data 324

Smarten

JANUARY 4, 2018

Extract, Transform and Load (ETL) refers to a process of connecting to data sources, integrating data from various data sources, improving data quality, aggregating it and then storing it in staging data source or data marts or data warehouses for consumption of various business applications including BI, Analytics and Reporting.

Data Warehouse 40

Data Warehouse OLAP Data Governance Optimization 40

Ontotext

FEBRUARY 12, 2024

It also breaks down the code and data monolith and distributes it across the domain teams, which results in better management and scalability. The data mesh concept will mitigate cognitive overload when building data-driven organizations that require intense technical, domain, and operational knowledge.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

DataKitchen

JANUARY 23, 2023

Data lineage and a data catalog are better together because they provide a more complete and accurate view of the data. It allows organizations to see how data is being used, where it is coming from, its quality, and how it is being transformed.

Testing 130

Testing Data Governance Data Quality Data-driven 130

Alation

NOVEMBER 22, 2022

What Is Data Governance In The Public Sector? Effective data governance for the public sector enables entities to ensure data quality, enhance security, protect privacy, and meet compliance requirements. With so much focus on compliance, democratizing data for self-service analytics can present a challenge.

Data Governance 52

Data Governance Metadata Data-driven Unstructured Data 52