erwin

SEPTEMBER 17, 2020

For example, automatically importing mappings from developers’ Excel sheets, flat files, Access and ETL tools into a comprehensive mappings inventory, complete with auto generated and meaningful documentation of the mappings, is a powerful way to support overall data governance. Data quality is crucial to every organization.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

AWS Big Data

MARCH 25, 2024

A RAG-based generative AI application can only produce generic responses based on its training data and the relevant documents in the knowledge base. For example, Amazon DynamoDB provides a feature for streaming CDC data to Amazon DynamoDB Streams or Kinesis Data Streams.

Data Lake 90

Data Lake Unstructured Data Management Modeling 90

CIO Business Intelligence

SEPTEMBER 26, 2023

Analyst firm Deep Analysis posits that the 400-plus vendor market for intelligent document processing alone could grow to $4 billion by the end of 2026. Data Architecture, Data Management, Privacy The returns on crafting effective information management strategies are significant.

Strategy 122

Strategy Data Architecture Management Metrics 122

CIO Business Intelligence

JUNE 20, 2022

This landmark document will look at how we can build on this momentum and apply the lessons challenges ahead of us, including tackling the COVID backlog and making the reforms that are vital to the future of health and care. EPR and NHS App targets.

Data Strategy 89

Data Strategy Strategy Digital Transformation Data Architecture 89

Cloudera

SEPTEMBER 28, 2020

Review the Upgrade document topic for the supported upgrade paths. Document the number of dev/test/production clusters. Document the operating system versions, database versions, and JDK versions. Review the JDK versions and determine if a JDK version change is needed and if so follow the documentation here to upgrade.

Testing 131

Testing Metadata Risk Data Science 131

CIO Business Intelligence

NOVEMBER 1, 2023

The challenge is obtaining that relevant information from an enterprise’s database, as classical database engines respond with records that are an exact match for a keyword, while relevant information may only match a broad concept — documents might refer to a product enhancement or improvement rather than an upgrade, for example.

Enterprise 128

Enterprise Cost-Benefit Unstructured Data Software 128

TDAN

AUGUST 3, 2021

Database standards are common practices and procedures that are documented and […]. Rigidly adhering to a standard, any standard, without being reasonable and using your ability to think through changing situations and circumstances is itself a bad standard.

Data Quality 116

Data Quality Data Architecture Modeling Management 116

CIO Business Intelligence

FEBRUARY 21, 2024

But the critical step of data preparation can’t be overlooked — and today, it uses decades-old technologies. They transform text queries and documents containing potential answers into high-dimensional vector spaces, facilitating the identification of content whose semantic content most closely aligns with the query.

Insurance 64

Insurance Unstructured Data Data Architecture Technology 64

AWS Big Data

NOVEMBER 9, 2023

This popular open-source tool for data warehouse transformations won out over other ETL tools for several reasons. The tool also offered desirable out-of-the-box features like data lineage, documentation, and unit testing. It’s raw, unprocessed data straight from the source.

Data Warehouse 104

Data Warehouse Testing Data Quality Reporting 104

TDAN

MAY 31, 2022

One very influential factor that can potentially undermine your data and document strategies is the natural and emotional reactions of people when things change. It is common to take great care in the selection and implementation of new technology.

Testing 52

Testing Interactive Strategy Software 52

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 112

Data Lake Analytics Dashboards Metrics 112

erwin

JULY 12, 2019

Modern, strategic data governance , which involves both IT and the business, enables organizations to plan and document how they will discover and understand their data within context, track its physical existence and lineage, and maximize its security, quality and value.

Data Governance 110

Data Governance Management Metadata Risk Management 110

TDAN

AUGUST 18, 2020

Consistent business meaning is important because distinctions between business terms are not typically well defined or documented. The business glossary is simple in concept, but it can be a challenge to structure, define and maintain shared business terminology. What are the standards for writing […].

Management 96

Management Metadata Data Architecture IT 96

Cloudera

AUGUST 30, 2022

It outlines a scenario in which “recently married people might want to change their names on their driver’s licenses or other documentation. That should be easy, but when agencies don’t share data or applications, they don’t have a unified view of people. Modern data architectures.

Data Architecture 76

Data Architecture Data Lake Metadata Data Warehouse 76

erwin

MAY 13, 2020

DM builds a more agile and governable data architecture. The DM process manages the design and maintenance lifecycle for data sources. DM governs the design and deployment of data across the enterprise. DM documents, standardizes and aligns any type of data no matter where it lives. .

Data Governance 93

Data Governance Modeling Enterprise Management 93

CIO Business Intelligence

SEPTEMBER 21, 2023

ML was used for sentiment analysis, and to scan documents, classify images, transcribe recordings, and other specific functions. One of the best immediate use cases is summarizing documents and extracting information from material, he says. But it’ll enable people to do higher-value work than they are currently able to do.”

Enterprise 127

Enterprise Consulting Modeling Cost-Benefit 127

erwin

DECEMBER 12, 2019

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

Octopai

JULY 9, 2020

It required banks to develop a data architecture that could support risk-management tools. Not only did the banks need to implement these risk-measurement systems (which depend on metrics arriving from distinct data dictionary tools), they also needed to produce reports documenting their use.

Insurance 86

Insurance Risk Management Machine Learning Metadata 86

AWS Big Data

APRIL 19, 2023

Independent data products often only have value if you can connect them, join them, and correlate them to create a higher order data product that creates additional insights. A modern data architecture is critical in order to become a data-driven organization.

Technology 80

Technology Data-driven Machine Learning Sales 80

Cloudera

DECEMBER 8, 2020

We have accomplished this significant improvement through supporting the deployment of the Cloudera Data Platform (CDP) Private Cloud Base on FIPS mode enabled RedHat Enterprise Linux (RHEL) and CentOS Operating Systems (OS), as well as through the use of FIPS 140-2 validated encryption modules. . Cloudera for Government.

IoT 63

IoT Enterprise Data Architecture Interactive 63

IBM Big Data Hub

FEBRUARY 9, 2023

Realize that a data governance program cannot exist on its own – it must solve business problems and deliver outcomes. Start by identifying business objectives, desired outcomes, key stakeholders, and the data needed to deliver these objectives. Don’t try to do everything at once!

Data Governance 82

Data Governance Business Objectives Strategy Data Quality 82

erwin

DECEMBER 12, 2019

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

Alation

MARCH 31, 2023

Actually, with Solomon-like wisdom, Zaidi and Thanaraj suggest a scenario where data fabric and data mesh work together — a Reese’s Peanut Butter Cup of data architecture, representing a “meshy fabric” scenario I presented last year. The active metadata helix Indeed, automation was on everyone’s minds.

Data Analytics 52

Data Analytics Analytics Metadata Data Governance 52

erwin

SEPTEMBER 19, 2019

These questions are the same ones we ask in data governance. They involve impact analysis, ownership and accountability, control and traceability – all of which effectively documented and managed business processes enable. Data sets are not important in and of themselves.

Data Governance 108

Data Governance Cost-Benefit Enterprise Modeling 108

AWS Big Data

FEBRUARY 8, 2023

Conclusion AWS Glue facilitated the data extraction, transformation, and loading process from different ERPs into Salesforce SMAX to improve Vyaire’s products and its related information visibility to service technicians and tech support users. To learn more about AWS Glue, check out AWS Glue Documentation.

Testing 73

Testing Data Integration Data Lake Enterprise 73

Alation

FEBRUARY 20, 2020

to catalog enterprise data by observing analyst behaviors. Our approach was contrasted with the traditional manual wiki of notes and documentation and labeled as a modern data catalog. We envisioned and learnt from the early production customer implementations that cataloging data wasn’t enough.

Metadata 52

Metadata Enterprise Data Processing Data Architecture 52

Ontotext

JULY 26, 2019

Examples of such continuous improvement are technological giants like Google and Amazon who use semantic technology principles to build better data architectures for better user experiences. Such an approach, no matter what name we use for it, is all about improving the way enterprises operate in an interconnected world.

Technology 75

Technology Enterprise Data Integration Management 75

Peter James Thomas

JANUARY 8, 2020

If you find the articles published on this site interesting and relevant to your work, then perhaps – like Neal Analytics – you would consider commissioning us to write a White Paper or some other document. If so, please just get in contact , or simply schedule an introductory ‘phone call.

Consulting 61

Consulting Data-driven Publishing Data Strategy 61

Ontotext

JULY 26, 2019

Examples of such continuous improvement are technological giants like Google and Amazon who use semantic technology principles to build better data architectures for better user experiences. Such an approach, no matter what name we use for it, is all about improving the way enterprises operate in an interconnected world.

Technology 40

Technology Data Integration Enterprise Structured Data 40

Peter James Thomas

MARCH 23, 2020

I won’t go into every aspect of this Data Strategy work, as the point of this article is instead to focus on the working from home element. However it is worth summarising the eventual number of interviews I held and documented: I have no idea how many ‘phone calls that equated to, but it must have been an awful lot.

Data Strategy 89

Data Strategy Strategy Insurance Interactive 89

AWS Big Data

APRIL 3, 2023

Systems Manager runs an AWS-RunShellScript SSM document to run the RSQL job on the EC2 instance. He has over 12 years of professional experience building and optimizing enterprise data warehouses and is passionate about enabling customers to realize the power of their data.

Data Warehouse 97

Data Warehouse Testing Data Lake Data-driven 97

Ontotext

JANUARY 10, 2024

As a start, such a platform would need to support two major design patterns: semantic knowledge hub and semantic data fabric. We call knowledge hub the pattern of using knowledge graphs to better manage documents and unstructured content. This helps improve the way relevant documents are found, recommended, and so on.

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72

CIO Business Intelligence

FEBRUARY 20, 2023

A candidate who earns the certification will have proved their ability to build bundle configurations, pricing, output documents, and renewals and amendments. The certification emphasizes testing, governance, and integration with external systems within an organization’s infrastructure.

Consulting 60

Consulting B2B Cost-Benefit Sales 60

Cloudera

JANUARY 30, 2023

Have you ever considered how much data a single person generates in a day? Every web document, scanned document, email, social media post, and media download? One estimate states that “ on average, people will produce 463 exabytes of data per day by 2025.” Now consider that the federal government has approximately 2.8

IoT 80

IoT Data Architecture Data Lake Machine Learning 80

Alation

MAY 31, 2023

This means that specialized roles such as data architects, which focus on modernizing data architecture to help meet business goals, are increasingly important to support data governance. What is a data architect? Their broad range of responsibilities include: Design and implement data architecture.

Data Governance 52

Data Governance Metadata Data Architecture Data Quality 52

IBM Big Data Hub

DECEMBER 1, 2023

Leading insurers in all geographies are implementing IBM’s data architectures and automation software on cloud. It also helps improve underwriting decisions, reduce fraud and control costs.

Insurance 106

Insurance Digital Transformation Unstructured Data Risk 106

IBM Big Data Hub

APRIL 11, 2023

The evaluation team should assess and document each system, decision point, and vendor by the population they serve, such as hourly workers, salaried employees, different pay groups, and countries. Policy orchestration within a data fabric architecture is an excellent tool that can simplify the complex AI audit processes.

Strategy 98

Strategy Data Architecture Data-driven Testing 98