AWS Big Data

SEPTEMBER 26, 2024

For many organizations, this centralized data store follows a data lake architecture. Although data lakes provide a centralized repository, making sense of this data and extracting valuable insights can be challenging. This is where Amazon Bedrock comes into play.

Data Lake 115

Data Lake Cost-Benefit Unstructured Data Modeling 115

CIO Business Intelligence

OCTOBER 9, 2024

The rise of generative AI (GenAI) felt like a watershed moment for enterprises looking to drive exponential growth with its transformative potential. As the technology subsists on data, customer trust and their confidential information are at stake—and enterprises cannot afford to overlook its pitfalls.

Strategy 143

Strategy Modeling Management Data Lake 143

David Menninger's Analyst Perspectives

JANUARY 21, 2025

While new and emerging capabilities might catch the eye, features that address data platform security, performance and availability remain some of the most significant deal-breakers when enterprises are considering potential data platform providers. This is especially true for mission-critical workloads. Regards, Matt Aslett

Data Lake 130

Data Lake IoT Cost-Benefit Enterprise 130

CIO Business Intelligence

FEBRUARY 27, 2025

A high hurdle many enterprises have yet to overcome is accessing mainframe data via the cloud. Data professionals need to access and work with this information for businesses to run efficiently, and to make strategic forecasting decisions through AI-powered data models.

Metadata 98

Metadata Data Lake Cost-Benefit Forecasting 98

erwin

SEPTEMBER 3, 2020

Why should you integrate data governance (DG) and enterprise architecture (EA)? Two of the biggest challenges in creating a successful enterprise architecture initiative are: collecting accurate information on application ecosystems and maintaining the information as application ecosystems change.

Data Governance 144

Data Governance Enterprise Risk Data Lake 144

AWS Big Data

MARCH 10, 2023

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

Data Lake 122

Data Lake Sales Data Warehouse Snapshot 122

DataKitchen

NOVEMBER 29, 2021

DataOps adoption continues to expand as a perfect storm of social, economic, and technological factors drive enterprises to invest in process-driven innovation. In 2022, data organizations will institute robust automated processes around their AI systems to make them more accountable to stakeholders. Data Gets Meshier.

Testing 245

Testing Data Lake Data Architecture Manufacturing 245

AWS Big Data

JUNE 10, 2024

Use cases for Hive metastore federation for Amazon EMR Hive metastore federation for Amazon EMR is applicable to the following use cases: Governance of Amazon EMR-based data lakes – Producers generate data within their AWS accounts using an Amazon EMR-based data lake supported by EMRFS on Amazon Simple Storage Service (Amazon S3)and HBase.

Data Lake 116

Data Lake Metadata Data Warehouse Data Processing 116

Jet Global

NOVEMBER 5, 2020

Ostensibly, the new product represents Microsoft’s transition to a newer, more cloud-friendly ERP for midsized enterprises. That stands for “bring your own database,” and it refers to a model in which core ERP data are replicated to a separate standalone database used exclusively for reporting. Option 3: Azure Data Lakes.

Data Lake 98

Data Lake OLAP Data Warehouse Unstructured Data 98

AWS Big Data

OCTOBER 14, 2024

Enterprise data is brought into data lakes and data warehouses to carry out analytical, reporting, and data science use cases using AWS analytical services like Amazon Athena , Amazon Redshift , Amazon EMR , and so on. foundation model (FM) in Amazon Bedrock as the LLM. The answer is yes.

Metadata 105

Metadata Data Lake Modeling Data Warehouse 105

DataKitchen

AUGUST 3, 2021

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. But first, let’s define the data mesh design pattern. The past decades of enterprise data platform architectures can be summarized in 69 words.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

DataKitchen

AUGUST 19, 2021

Data mesh and DataOps provide the organization, enterprise architecture, and workflow automation that together enable a relatively small data team to address the analytics needs of hundreds of active business users. Figure 1: Data requirements for phases of the drug product lifecycle. The new Recipes run, and BOOM!

Data Warehouse 246

Data Warehouse Data Lake Manufacturing Testing 246

AWS Big Data

OCTOBER 21, 2024

Data is the most significant asset of any organization. However, enterprises often encounter challenges with data silos, insufficient access controls, poor governance, and quality issues. Embracing data as a product is the key to address these challenges and foster a data-driven culture.

Sales 115

Sales Data-driven Data Processing Key Performance Indicator 115

AWS Big Data

DECEMBER 12, 2024

One-time and complex queries are two common scenarios in enterprise data analytics. Complex queries, on the other hand, refer to large-scale data processing and in-depth analysis based on petabyte-level data warehouses in massive data scenarios. Here, data modeling uses dbt on Amazon Redshift.

Snapshot 97

Snapshot Recreation/Entertainment Experimentation Data Lake 97

AWS Big Data

SEPTEMBER 13, 2023

A modern data architecture is an evolutionary architecture pattern designed to integrate a data lake, data warehouse, and purpose-built stores with a unified governance model. Of those tables, some are larger (such as in terms of record volume) than others, and some are updated more frequently than others.

Data Lake 111

Data Lake Data Processing Metadata Snapshot 111

AWS Big Data

FEBRUARY 26, 2025

This evaluation, we feel, critically examines vendors capabilities to address key service needs, including data engineering, operational data integration, modern data architecture delivery, and enabling less-technical data integration across various deployment models.

Data Integration 103

Data Integration Data Lake Data Warehouse Unstructured Data 103

Jet Global

SEPTEMBER 4, 2020

Consultants and developers familiar with the AX data model could query the database using any number of different tools, including a myriad of different report writers. Data entities are more secure and arguably easier to master than the relational database model, but one downside is there are lots of them! Data Lakes.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

CIO Business Intelligence

AUGUST 14, 2024

Between building gen AI features into almost every enterprise tool it offers, adding the most popular gen AI developer tool to GitHub — GitHub Copilot is already bigger than GitHub when Microsoft bought it — and running the cloud powering OpenAI, Microsoft has taken a commanding lead in enterprise gen AI. That’s risky.”

Enterprise 136

Enterprise Cost-Benefit Experimentation Modeling 136

IBM Big Data Hub

MAY 9, 2023

Data must be laboriously collected, curated, and labeled with task-specific annotations to train AI models. Building a model requires specialized, hard-to-find skills — and each new task requires repeating the process. ” These large models have lowered the cost and labor involved in automation.

Enterprise 128

Enterprise Technology Modeling Cost-Benefit 128

erwin

AUGUST 31, 2023

Q: Is data modeling cool again? In today’s fast-paced digital landscape, data reigns supreme. The data-driven enterprise relies on accurate, accessible, and actionable information to make strategic decisions and drive innovation. A: It always was and is getting cooler!!

Data-driven 98

Data-driven Modeling Enterprise Structured Data 98

CIO Business Intelligence

FEBRUARY 20, 2025

When building a machine-learning-powered tool to predict the maintenance needs of its customers, Ensono found that its customers used multiple old apps to collect incident tickets, but those apps stored incident data in very different formats, with inconsistent types of data collected, he says.

Insurance 108

Insurance Cost-Benefit Unstructured Data Data Lake 108

O'Reilly on Data

OCTOBER 19, 2021

This is both frustrating for companies that would prefer making ML an ordinary, fuss-free value-generating function like software engineering, as well as exciting for vendors who see the opportunity to create buzz around a new category of enterprise software. The new category is often called MLOps. Compute.

IT 364

IT Testing Experimentation Software 364

CIO Business Intelligence

APRIL 8, 2025

I aim to outline pragmatic strategies to elevate data quality into an enterprise-wide capability. Key recommendations include investing in AI-powered cleansing tools and adopting federated governance models that empower domains while ensuring enterprise alignment. The patterns are consistent across industries.

Data Quality 102

Data Quality Data-driven Key Performance Indicator Metadata 102

DataKitchen

DECEMBER 7, 2021

In the book, author Zhamak Dehghani reveals that, despite the time, money, and effort poured into them, data warehouses and data lakes fail when applied at the scale and speed of today’s organizations. A distributed data mesh is a better choice. The book will be available from O’Reilly Media here.

Data-driven 246

Data-driven Data Governance Big Data Data Science 246

CIO Business Intelligence

SEPTEMBER 21, 2023

AI is now a board-level priority Last year, AI consisted of point solutions and niche applications that used ML to predict behaviors, find patterns, and spot anomalies in carefully curated data sets. Today’s foundational models are jacks-of-all-trades. All of PwC’s clients are having this discussion, he says. Gen AI took a few months.

Enterprise 130

Enterprise Consulting Modeling Cost-Benefit 130

CIO Business Intelligence

APRIL 26, 2024

Count TransUnion among the rising tide of enterprises evolving their identities thanks to IT. “We The power of productizing data TransUnion’s OneTru has been made possible by the company’s migration to AWS, dubbed “Project Rise,” which is slated for completion by year’s end.

Modeling 114

Modeling IT Machine Learning Data Governance 114

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 111

Enterprise Data Warehouse Data Lake Optimization 111

AWS Big Data

MAY 29, 2024

Many organizations use external identity providers (IdPs) such as Okta or Microsoft Azure Active Directory to manage their enterprise user identities. Later in this post, we also briefly touch upon using CloudTrail Lake to query the data access events. In the following sections, we demonstrate how to build this architecture.

Data Lake 115

Data Lake Enterprise Management Business Intelligence 115

AWS Big Data

APRIL 24, 2025

Scalability ABAC systems are more scalable for larger enterprises because they can handle a large number of users and resources without requiring a large number of roles. Attribute-based access control overview Previously, within SageMaker Lakehouse, Lake Formation granted access to resources based on the identity of a requesting user.

Sales 89

Sales Data Lake Management Data-driven 89

CIO Business Intelligence

OCTOBER 25, 2023

From IT, to finance, marketing, engineering, and more, AI advances are causing enterprises to re-evaluate their traditional approaches to unlock the transformative potential of AI. What can enterprises learn from these trends, and what future enterprise developments can we expect around generative AI?

Enterprise 133

Enterprise Manufacturing Risk Data-driven 133

AWS Big Data

JULY 21, 2023

Data-driven organizations treat data as an asset and use it across different lines of business (LOBs) to drive timely insights and better business decisions. This leads to having data across many instances of data warehouses and data lakes using a modern data architecture in separate AWS accounts.

Data Lake 98

Data Lake Data Warehouse Marketing Management 98

AWS Big Data

DECEMBER 4, 2024

Under the federated mesh architecture, each divisional mesh functions as a node within the broader enterprise data mesh, maintaining a degree of autonomy in managing its data products. This model balances node or domain-level autonomy with enterprise-level oversight, creating a scalable and consistent framework across ANZ.

Metadata 105

Metadata Data Governance Data Quality Data-driven 105

AWS Big Data

JUNE 20, 2023

It manages large collections of files as tables, and it supports modern analytical data lake operations such as record-level insert, update, delete, and time travel queries. Data labeling is required for various use cases, including forecasting, computer vision, natural language processing, and speech recognition.

Data Lake 103

Data Lake Data Science Recreation/Entertainment Data-driven 103

CIO Business Intelligence

JULY 31, 2024

This year, however, Salesforce has accelerated its agenda, integrating much of its recent work with large language models (LLMs) and machine learning into a low-code tool called Einstein 1 Studio. Einstein 1 Studio is a set of low-code tools to create, customize, and embed AI models in Salesforce workflows. What is Einstein 1 Studio?

Data Lake 119

Data Lake IT Sales Experimentation 119

AWS Big Data

APRIL 24, 2023

Building a data lake on Amazon Simple Storage Service (Amazon S3) provides numerous benefits for an organization. However, many use cases, like performing change data capture (CDC) from an upstream relational database to an Amazon S3-based data lake, require handling data at a record level.

Data Lake 98

Data Lake Data Governance Machine Learning Cost-Benefit 98

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 111

Enterprise Data Warehouse Snapshot Cost-Benefit 111

erwin

DECEMBER 17, 2020

What is Microsoft’s Common Data Model (CDM), and why is it so powerful? The same is true for data, with a number of vendors creating data models by vertical industry (financial services, healthcare, etc.) and making them commercially available to improve how organizations understand and work with their data assets.

Modeling 90

Modeling Metadata Data-driven Data Lake 90