AWS Big Data

FEBRUARY 29, 2024

However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications. Implement data privacy policies. Implement data quality by data type and source.

Data Governance 95

Data Governance Unstructured Data Metadata Data Lake 95

CIO Business Intelligence

MARCH 24, 2023

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time. The program must introduce and support standardization of enterprise data.

Data Governance 142

Data Governance Management Metadata Data Quality 142

erwin

FEBRUARY 28, 2024

While the essence of success in data governance is people and not technology, having the right tools at your fingertips is crucial. Technology is an enabler, and for data governance this is essentially having an excellent metadata management tool. Next to data governance, data architecture is really embedded in our DNA.

Metadata 52

Metadata Data Governance Data Quality Technology 52

erwin

MARCH 30, 2020

To marry the epidemiological data to the population data it will require a tremendous amount of data intelligence about the: Source of the data; Currency of the data; Quality of the data; and. Unraveling Data Complexities with Metadata Management. Data lineage to support impact analysis.

Metadata 122

Metadata IT Data Governance Data Quality 122

Ontotext

NOVEMBER 18, 2021

And all of them are asking hard questions: “Can you integrate my data, with my particular format?”, “How well can you scale?”, “How many visualizations do you offer?”. Nowadays, data analytics doesn’t exist on its own. You have to take care of data extraction, transformation and loading, and of visualization.

Visualization 98

Visualization Reporting Metadata Enterprise 98

erwin

APRIL 29, 2020

These tools range from enterprise service bus (ESB) products, data integration tools; extract, transform and load (ETL) tools, procedural code, application program interfaces (API)s, file transfer protocol (FTP) processes, and even business intelligence (BI) reports that further aggregate and transform data. Who are the data owners?

Data Governance 111

Data Governance Key Performance Indicator Metadata Data Quality 111

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

erwin

DECEMBER 3, 2020

Being able to integrate all data touchpoints, including erwin DM for data modeling, Denodo for data visualization, and Jira for ticketing, has been key. Using erwin DI, customers are powering comprehensive data governance initiatives, cloud migration and other massive digital transformation projects.

Metadata 141

Metadata Data Governance Data-driven Digital Transformation 141

Alation

FEBRUARY 7, 2023

The product collected an impressive amount of metadata, from the user interface to the database structure. It then translated all that metadata into an image resembling a spider’s web. Back then, visualizing impact analysis seemed futuristic with great promise. That was my earliest taste of data lineage.

Metadata 52

Metadata Data Warehouse Visualization Data Quality 52

erwin

AUGUST 7, 2019

A data catalog benefits organizations in a myriad of ways. With the right data catalog tool, organizations can automate enterprise metadata management – including data cataloging, data mapping, data quality and code generation for faster time to value and greater accuracy for data movement and/or deployment projects.

Metadata 90

Metadata Data Governance Data Quality Data Warehouse 90

CIO Business Intelligence

NOVEMBER 22, 2022

Data fabric is an architecture that enables the end-to-end integration of various data pipelines and cloud environments through the use of intelligent and automated systems. The fabric, especially at the active metadata level, is important, Saibene notes.

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

Octopai

JANUARY 19, 2020

Metadata Management is the Key to Successful Data Governance Learn more in the webinar, "Metadata Management Automation for the Governance Minded" Watch the Webinar! BCBS 239 and Automated Metadata Management Tools. You may recognize the common thread running through all of these principles: Metadata.

Metadata 61

Metadata Risk Management Business Intelligence Risk 61

Octopai

MAY 31, 2022

On the occasions when a report or dashboard error does show up, it doesn’t take long to do some BI root cause analysis and track down the source of the error using a data lineage visualization. Bonus tool: active metadata management. An active metadata management tool adds a maître d’ to self-serve analytics.

Management 52

Management Metadata Business Intelligence ROI 52

Octopai

JANUARY 21, 2020

How much time has your BI team wasted on finding data and creating metadata management reports? BI groups spend more than 50% of their time and effort manually searching for metadata. In fact, BI projects used to take many months to complete and require huge numbers of IT professionals to extract data. Cube to the rescue.

OLAP 56

OLAP Metadata Online Analytical Processing Data Quality 56

Alation

DECEMBER 21, 2022

Master Data Management (MDM) and data catalog growth are accelerating because organizations must integrate more systems, comply with privacy regulations, and address data quality concerns. What Is Master Data Management (MDM)? Data Catalog and Master Data Management. Assess Data Quality.

Management 52

Management Data Quality Metadata Testing 52

Ontotext

SEPTEMBER 15, 2020

The Data Fabric paradigm combines design principles and methodologies for building efficient, flexible and reliable data management ecosystems. Knowledge Graphs are the Warp and Weft of a Data Fabric. To implement any Data Fabric approach, it is essential to be able to understand the context of data.

Metadata 69

Metadata Knowledge Discovery Data Quality Strategy 69

Octopai

APRIL 5, 2020

The solution to such problems is automated BI intelligence – a comprehensive platform that includes automated data lineage, data discovery, and business glossary. Octopai empowers users with visual maps that are comprehensive in their ability to explain data from various angles and to trace a data point from source to endpoint.

Metadata 52

Metadata Data Quality Reporting Management 52

IBM Big Data Hub

MAY 9, 2022

Data privacy laws such as the GDPR in the EU, CCPA in California and PIPEDA in Canada have been enacted at the same time businesses are revitalizing efforts to establish data quality, not just data volume. Poor data quality costs organizations an average of $12.9 million each year [1] and $1.2 28, 2021. [2].

Management 57

Management Data Quality Metadata Data Integration 57

AWS Big Data

MARCH 7, 2023

Sources Data can be loaded from multiple sources, such as systems of record, data generated from applications, operational data stores, enterprise-wide reference data and metadata, data from vendors and partners, machine-generated data, social sources, and web sources.

Analytics 72

Analytics Data Warehouse Data Lake Metadata 72

IBM Big Data Hub

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. Data quality Data quality is essentially the measure of data integrity.

Data Quality 65

Data Quality Data Integration Metadata Cost-Benefit 65

Octopai

JUNE 24, 2019

This maintains a high priority in your data governance strategy. As such, your chosen tool must provide data quality management, perform data movement, track modifications of metadata objects, support cascade changes, expose metadata, and be capable of printing visual representations of data lineage.

Data Governance 42

Data Governance Metadata Unstructured Data Software 42

Ontotext

JUNE 22, 2023

On top of that, data is sometimes unreliable , and inaccurate or missing metadata makes it hard to decide which information to trust. It can also be easily maintained and upgraded, which lowers the costs of adding new data and maintaining data updates.

Metrics 52

Metrics Statistics Visualization Metadata 52

Octopai

JANUARY 31, 2021

The particular episode we recommend looks at how WeWork struggled with understanding their data lineage so they created a metadata repository to increase visibility. Agile Data. Another podcast we think is worth a listen is Agile Data. TDWI – Philip Russom.

Data Governance 57

Data Governance Data Processing Data Quality Metadata 57

Alation

JUNE 2, 2022

How Data Lineage Is a Use Case in ML. Data lineage is one example of a use case in which ML can play a pivotal role. Data lineage is the process of recording and visualizing data flowing from data sources to consumption. Data lineage allows companies to troubleshoot errors in data processes.

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

Ontotext

JULY 6, 2023

This shift of both a technical and an outcome mindset allows them to establish a centralized metadata hub for their data assets and effortlessly access information from diverse systems that previously had limited interaction. There are four groups of data that are naturally siloed: Structured data (e.g.,

Cost-Benefit 52

Cost-Benefit Experimentation Metadata Risk 52

BizAcuity

MARCH 29, 2019

Data lakes are centralized repositories that can store all structured and unstructured data at any desired scale. The power of the data lake lies in the fact that it often is a cost-effective way to store data. Numbers are only good if the data quality is good.

Data Lake 102

Data Lake Unstructured Data Cost-Benefit Data Quality 102

Ontotext

MARCH 8, 2023

Solution Outcomes: A semantic recommendation service that is beating accuracy benchmarks and replacing manual processes aggregating content – that is supporting higher-quality, more advanced, and targeted recommendations with clear reasons. million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Alation

MAY 4, 2023

Are you an aspiring data scientist , or just want to understand the benefits of integrating data catalogs with visualization tools? In today’s ever-growing world of data, having an easy way to gain insights quickly is essential. What are data visualization tools?

Visualization 52

Visualization Metadata Data Governance KPI 52

DataKitchen

SEPTEMBER 21, 2023

These layers help teams delineate different stages of data processing, storage, and access, offering a structured approach to data management. In the context of Data in Place, validating data quality automatically with Business Domain Tests is imperative for ensuring the trustworthiness of your data assets.

Testing 176

Testing Data Quality Predictive Modeling Metrics 176

Alation

MAY 4, 2023

Are you an aspiring data scientist , or just want to understand the benefits of integrating data catalogs with visualization tools? In today’s ever-growing world of data, having an easy way to gain insights quickly is essential. What are data visualization tools?

Visualization 40

Visualization Metadata Data Governance KPI 40

AWS Big Data

NOVEMBER 16, 2023

Through Amazon Redshift in-memory result set caching and compilation caching, workloads ranging from dashboarding to visualization to business intelligence (BI) that run repeat queries experience a significant performance boost. Chargeback metadata Amazon Redshift provides different pricing models to cater to different customer needs.

Enterprise 84

Enterprise Data Warehouse Snapshot Cost-Benefit 84

AWS Big Data

DECEMBER 18, 2023

AWS Step Functions is a fully managed visual workflow service that enables you to build complex data processing pipelines involving a diverse set of extract, transform, and load (ETL) technologies such as AWS Glue , Amazon EMR , and Amazon Redshift. There are multiple tables related to customers and order data in the RDS database.

Metadata 121

Metadata Visualization Data Lake Data-driven 121

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data. Then, you transform this data into a concise format.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

Alation

SEPTEMBER 22, 2022

Overseeing data quality and ensuring proper usage represent two core reasons. Data pipelines contain valuable information that can be used to improve data quality and ensure data is used properly. As organizations race to become data-driven, more parts of the organization need data intelligence.

Metadata 52

Metadata Data-driven Data Quality Visualization 52

Alation

JULY 19, 2022

Get the data. Explore the data. Model the data. Communicate and visualize the results. A data catalog can assist directly with every step, but model development. How Data Catalogs Help Data Scientists Ask Better Questions. Modern data catalogs also facilitate data quality checks.

Metadata 59

Metadata Data Quality Statistics Data Science 59

Smart Data Collective

SEPTEMBER 26, 2021

Everyone has to manage raw data at one point or another; yet, not everybody stores it in a way that’s useful for further analysis or comparison to other data sets. As data sets become bigger, it becomes harder to visualize information. Draw a chart highlighting each endpoint in your data.

Metadata 96

Metadata Visualization Unstructured Data Data mining 96

AWS Big Data

FEBRUARY 1, 2023

We also used AWS Lambda for data processing. To further optimize and improve the developer velocity for our data consumers, we added Amazon DynamoDB as a metadata store for different data sources landing in the data lake. Clients access this data store with an API’s.

Optimization 52

Optimization Forecasting Data Lake Metadata 52