DataKitchen

NOVEMBER 5, 2024

This architecture is valuable for organizations dealing with large volumes of diverse data sources, where maintaining accuracy and accessibility at every stage is a priority. It sounds great, but how do you prove the data is correct at each layer? How do you ensure data quality in every layer ?

Data Quality 198

Data Quality Testing Metrics Reporting 198

CIO Business Intelligence

APRIL 8, 2025

We also examine how centralized, hybrid and decentralized data architectures support scalable, trustworthy ecosystems. As data-centric AI, automated metadata management and privacy-aware data sharing mature, the opportunity to embed data quality into the enterprises core has never been more significant.

Data Quality 101

Data Quality Data-driven Key Performance Indicator Metadata 101

Cloudera

SEPTEMBER 29, 2022

Each of these trends claim to be complete models for their data architectures to solve the “everything everywhere all at once” problem. Data teams are confused as to whether they should get on the bandwagon of just one of these trends or pick a combination. First, we describe how data mesh and data fabric could be related.

Data Architecture 74

Data Architecture Data Warehouse Metadata Sales 74

CIO Business Intelligence

MARCH 25, 2025

Build up: Databases that have grown in size, complexity, and usage build up the need to rearchitect the model and architecture to support that growth over time.

Risk 140

Risk Cost-Benefit Data-driven Digital Transformation 140

CIO Business Intelligence

OCTOBER 13, 2023

Data architecture is a complex and varied field and different organizations and industries have unique needs when it comes to their data architects. Solutions data architect: These individuals design and implement data solutions for specific business needs, including data warehouses, data marts, and data lakes.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

AWS Big Data

NOVEMBER 7, 2024

Refer to this BladeBridge documentation to get more details on SQL and expression conversion. He has over 13 years of professional experience building and optimizing enterprise data warehouses and is passionate about enabling customers to realize the power of their data. This line ending also can be replaced with other breakers.

Data Warehouse 105

Data Warehouse Reporting Big Data Data Lake 105

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

CIO Business Intelligence

DECEMBER 11, 2024

Furthermore, generally speaking, data should not be split across multiple databases on different cloud providers to achieve cloud neutrality. Not my original quote, but a cardinal sin of cloud-native data architecture is copying data from one location to another.

Management 110

Management Data Governance Data Science Reporting 110

AWS Big Data

APRIL 8, 2025

In modern data architectures, Apache Iceberg has emerged as a popular table format for data lakes, offering key features including ACID transactions and concurrent write support. For more detailed configuration, refer to Write properties in the Iceberg documentation.

Snapshot 138

Snapshot Management Metadata Big Data 138

CIO Business Intelligence

MARCH 18, 2024

RAG optimizes LLMs by giving them the ability to reference authoritative knowledge bases outside their training data. “There are tons of documents that are not residing in an SAP system,” Herzig said. Artificial Intelligence, Data Architecture, Data Science, Digital Transformation, Generative AI, IT Leadership, Nvidia, SAP

Digital Transformation 117

Digital Transformation Optimization Data Science Modeling 117

CIO Business Intelligence

NOVEMBER 21, 2022

Taking this strategic view of the data asset and making the data the platform for a successful business is also a fundamental change in the role of the CIO. For more information on how you can create a data platform that gives the organization the same certainty for its information as it has for its money, visit our website.

Data Architecture 121

Data Architecture Management Strategy Marketing 121

erwin

JUNE 25, 2020

The Difference Between Technical Architecture and Enterprise Architecture. We previously have discussed the difference between data architecture and EA plus the difference between solutions architecture and EA. Powerful analytic tools to better understand an organization’s architecture – such as impact analysis.

Enterprise 144

Enterprise Data Architecture Data-driven Cost-Benefit 144

CIO Business Intelligence

MARCH 24, 2023

It must be clear to all participants and auditors how and when data-related decisions and controls were introduced into the processes. Data-related decisions, processes, and controls subject to data governance must be auditable. IBM Data Governance IBM Data Governance leverages machine learning to collect and curate data assets.

Data Governance 142

Data Governance Management Metadata Data Quality 142

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 132

Testing Metadata Risk Data Science 132

AWS Big Data

JUNE 12, 2024

This is covered using an AWS Systems Manager automation document (SSM document). The SSM document is based on the AWS document AWSConfigRemediation-DeleteRedshiftCluster. The SSM document is based on the AWS document AWSConfigRemediation-DeleteRedshiftCluster. schemaVersion: '0.3' Clusters[0].ClusterStatus'

Data-driven 115

Data-driven Snapshot Optimization Management 115

AWS Big Data

OCTOBER 30, 2024

He has over 13 years of professional experience building and optimizing enterprise data warehouses and is passionate about enabling customers to realize the power of their data. He specializes in migrating enterprise data warehouses to AWS Modern Data Architecture.

Data Warehouse 111

Data Warehouse Sales Data Lake Recreation/Entertainment 111

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

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 105

Data Strategy Strategy Digital Transformation Data Architecture 105

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

erwin

OCTOBER 24, 2019

Organizations are dealing with numerous data types and data sources that were never designed to work together and data infrastructures that have been cobbled together over time with disparate technologies, poor documentation and with little thought for downstream integration.

Metadata 104

Metadata Management Data-driven Data Architecture 104

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 83

IoT Data Architecture Data Lake Machine Learning 83

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 124

Strategy Data Architecture Metrics Management 124

AWS Big Data

OCTOBER 30, 2024

This is part two of a three-part series where we show how to build a data lake on AWS using a modern data architecture. This post shows how to load data from a legacy database (SQL Server) into a transactional data lake ( Apache Iceberg ) using AWS Glue. format(add_column)).select("DATA_TYPE").toPandas().iterrows())[0]

Data Lake 105

Data Lake Data Processing Optimization Machine Learning 105

CIO Business Intelligence

SEPTEMBER 17, 2024

The platform also provides automation tools such as auto-filling, document scanning, prompting, and anomaly detection. Advice to enterprise leaders In choosing any AI vendor, it’s important that enterprise leaders look at data architecture, as well as value creation and adoption rates, North Rizza advised.

IT 121

IT Recreation/Entertainment Finance Reporting 121

AWS Big Data

JANUARY 6, 2025

Follow the documentation to clean up the Google resources. Conclusion In this post, we walked you through the process of using Amazon AppFlow to integrate data from Google Ads and Google Sheets. He specializes in migrating enterprise data warehouses to AWS Modern Data Architecture.

Analytics 98

Analytics Data Warehouse Metrics Big Data 98

BI-Survey

AUGUST 21, 2020

They focus less on data marts, tend to extend the data warehouse with a data lake and utilize analytic databases and real-time processing more frequently. They are opting for cloud data services more frequently. For example, varied data types are handled with new data modeling approaches supported by appropriate tools.

Data Warehouse 98

Data Warehouse Data Lake Data Governance Data Architecture 98

CIO Business Intelligence

NOVEMBER 7, 2023

Opting for a centralized data and reporting model rather than training and embedding analysts in individual departments has allowed us to stay nimble and responsive to meet urgent needs, and prevented us from spending valuable resources on low-value data projects which often had little organizational impact,” Higginson says.

Data Warehouse 142

Data Warehouse Digital Transformation Data-driven Reporting 142

Sisense

JULY 6, 2020

Its main purpose is to establish an enterprise data management strategy. That includes the creation of fundamental documents that define policies, procedures, roles, tasks, and responsibilities throughout the organization. These regulations, ultimately, ensure key business values: data consistency, quality, and trustworthiness.

Enterprise 98

Enterprise Management Data Architecture Data-driven 98

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 132

Enterprise Cost-Benefit Unstructured Data Software 132

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 121

Data Lake Unstructured Data Management Snapshot 121

CIO Business Intelligence

AUGUST 21, 2024

Then there’s the risk of malicious code injections, where the code is hidden inside documents read by an AI agent, and the AI then executes the code. For example, OpenAI’s GPT-4o, which is multimodal, is used to handle scanned documents or images such as photographs of damage.

Risk 136

Risk Insurance Cost-Benefit Software 136

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 87

Strategy Data Architecture Data-driven Testing 87

CIO Business Intelligence

MARCH 6, 2024

Invoices as an object inside an enterprise could be an email or a PDF document; it could be a text file,” Chirapurath said. To illustrate this point, he gave the example of asking a copilot to generate a dashboard that shows all invoices. SAC has to be able to understand all those things and then provide links to it.

Unstructured Data 129

Unstructured Data Dashboards Business Intelligence Data Governance 129

AWS Big Data

OCTOBER 25, 2023

Text, images, audio, and videos are common examples of unstructured data. Most companies produce and consume unstructured data such as documents, emails, web pages, engagement center phone calls, and social media. Amazon Textract – You can use this ML service to extract metadata from scanned documents and images.

Unstructured Data 133

Unstructured Data Metadata Management Analytics 133

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

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 98

Insurance Risk Management Machine Learning Metadata 98

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 126

Data Warehouse Testing Data Quality Reporting 126