Cloudera

JUNE 2, 2022

Since 2015, the Cloudera DataFlow team has been helping the largest enterprise organizations in the world adopt Apache NiFi as their enterprise standard data movement tool. This need has generated a market opportunity for a universal data distribution service. Why does every organization need it when using a modern data stack?

Enterprise 99

Enterprise Data Lake Data Collection Data-driven 99

erwin

MAY 2, 2022

How to create a solid foundation for data modeling of OLTP systems. As you undertake a cloud database migration , a best practice is to perform data modeling as the foundation for well-designed OLTP databases. This makes mastering basic data modeling techniques and avoiding common pitfalls imperative. Data modeling basics.

Modeling 98

Modeling Insurance Cost-Benefit Data Warehouse 98

Data Virtualization

SEPTEMBER 28, 2023

Reading Time: 2 minutes In the realm of logical architectures and data virtualization, one question consistently arises: Can these architectures deliver the performance required for complex analytics scenarios? Today, we’ll explore the answer to this pressing question and dive into the game-changing integration of.

Data Integration 65

Data Integration Management Analytics Data Lake 65

AWS Big Data

FEBRUARY 9, 2023

Customers across industries seek meaningful insights from the data captured in their Customer Relationship Management (CRM) systems. To achieve this, they combine their CRM data with a wealth of information already available in their data warehouse, enterprise systems, or other software as a service (SaaS) applications.

Data Warehouse 74

Data Warehouse Data-driven Snapshot Testing 74

Alation

APRIL 14, 2023

Last week, the Alation team had the privilege of joining IT professionals, business leaders, and data analysts and scientists for the Modern Data Stack Conference in San Francisco. The show floor was buzzing with industry experts, networking and sharing valuable insights on the latest developments in the data space.

Data Warehouse 52

Data Warehouse Data-driven Digital Transformation Metadata 52

Data Virtualization

FEBRUARY 17, 2022

Reading Time: 3 minutes Data is at the center of every company. The post What is Data Virtualization? Understanding the Concept and its Advantages appeared first on Data Virtualization blog - Data Integration and Modern Data Management Articles, Analysis and Information.

IT 82

IT Data Integration Management Data Lake 82

IBM Big Data Hub

JANUARY 5, 2023

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

Data Virtualization

APRIL 5, 2023

However, it has also brought massive and growing data volumes that can be either a goldmine or an indecipherable pool, depending on each organization’s ability. The post Data Mesh and the Future of Financial Services appeared first on Data Virtualization blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Data Integration 52

Data Integration Management Data Lake IT 52

Data Virtualization

APRIL 5, 2023

However, it has also brought massive and growing data volumes that can be either a goldmine or an indecipherable pool, depending on each organization’s ability. The post Data Mesh and the Future of Financial Services appeared first on Data Virtualization blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Data Integration 52

Data Integration Management Data Lake IT 52

CIO Business Intelligence

JULY 13, 2022

Since 2015, the Cloudera DataFlow team has been helping the largest enterprise organizations in the world adopt Apache NiFi as their enterprise standard data movement tool. This need has generated a market opportunity for a universal data distribution service. Why does every organization need it when using a modern data stack?

Enterprise 60

Enterprise Data Lake Data Collection Data-driven 60

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

Data Virtualization

MARCH 23, 2023

The post 5 Trends in Financial Services That Will Change How You Think about Your Data appeared first on Data Virtualization blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Interactive 52

Interactive Data Integration Technology Management 52

Data Virtualization

MARCH 23, 2023

The post <strong>5 Trends in Financial Services That Will Change How You Think about Your Data</strong> appeared first on Data Virtualization blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Interactive 52

Interactive Data Integration Technology Management 52

Alation

JULY 28, 2022

There was a time when most CIOs would never consider putting their crown jewels — AKA customer data and associated analytics — into the cloud. But today, there is a magic quadrant for cloud databases and warehouses comprising more than 20 vendors. And what must organizations overcome to succeed at cloud data warehousing ?

Data Warehouse 69

Data Warehouse Cost-Benefit Data Governance Data-driven 69

Cloudera

MAY 16, 2019

The conference provides a useful opportunity to reflect on the rapid evolution we’ve seen in the Data Integration and Management space, much of it driven by the innovations that Cloudera and the open source community have been delivering. The traditional Data Warehouse ETL process has splintered into many smaller components.

Analytics 40

Analytics Data Warehouse Data-driven Data Integration 40

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. But the attempts to standardize data across the entire enterprise haven’t produced the desired results.

Data Governance 40

Data Governance Risk Metadata Management 40

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

datapine

MAY 29, 2019

That’s a fact in today’s competitive business environment that requires agile access to a data storage warehouse , organized in a manner that will improve business performance, deliver fast, accurate, and relevant data insights. One of the BI architecture components is data warehousing. Data integration.

Business Intelligence 196

Business Intelligence Data Warehouse Dashboards Visualization 196

Ontotext

MARCH 8, 2023

Gartner predicts that graph technologies will be used in 80% of data and analytics innovations by 2025, up from 10% in 2021. Use Case #1: Customer 360 / Enterprise 360 Customer data is typically spread across multiple applications, departments, and regions. Several factors are driving the adoption of knowledge graphs. million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

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

AWS Big Data

OCTOBER 27, 2023

Data integration is the foundation of robust data analytics. It encompasses the discovery, preparation, and composition of data from diverse sources. In the modern data landscape, accessing, integrating, and transforming data from diverse sources is a vital process for data-driven decision-making.

Analytics 95

Analytics Visualization Data Integration Cost-Benefit 95

Alation

JANUARY 17, 2023

Chances are, you’ve heard of the term “modern data stack” before. In this article, I will explain the modern data stack in detail, list some benefits, and discuss what the future holds. What Is the Modern Data Stack? It is known to have benefits in handling data due to its robustness, speed, and scalability.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

erwin

FEBRUARY 7, 2019

Organization’s cannot hope to make the most out of a data-driven strategy, without at least some degree of metadata-driven automation. The volume and variety of data has snowballed, and so has its velocity. So it’s safe to say that organizations can’t reap the rewards of their data without automation.

Metadata 96

Metadata Insurance Data-driven Cost-Benefit 96

Cloudera

JULY 11, 2022

The need for data fabric. As Cloudera CMO David Moxey outlined in his blog , we live in a hybrid data world. Data is growing and continues to accelerate its growth. Cloudera data fabric and analyst acclaim. Data fabrics are one of the more mature modern data architectures. As a result, it’s getting ??progressively

Data Architecture 104

Data Architecture Data-driven Cost-Benefit Data Warehouse 104

AWS Big Data

JULY 19, 2023

Amazon Redshift is a fully managed and petabyte-scale cloud data warehouse that is used by tens of thousands of customers to process exabytes of data every day to power their analytics workload. You can structure your data, measure business processes, and get valuable insights quickly can be done by using a dimensional model.

Modeling 67

Modeling Sales Data Warehouse Snapshot 67

Smart Data Collective

SEPTEMBER 8, 2021

The ETL process is defined as the movement of data from its source to destination storage (typically a Data Warehouse) for future use in reports and analyzes. The data is initially extracted from a vast array of sources before transforming and converting it to a specific format based on business requirements.

Data Warehouse 94

Data Warehouse Data Integration Marketing Software 94

IBM Big Data Hub

APRIL 27, 2022

Data fabric and data mesh are emerging data management concepts that are meant to address the organizational change and complexities of understanding, governing and working with enterprise data in a hybrid multicloud ecosystem. The good news is that both data architecture concepts are complimentary.

Management 87

Management Metadata Data Architecture Data Lake 87

DataKitchen

APRIL 13, 2021

Read the complete blog below for a more detailed description of the vendors and their capabilities. This is not surprising given that DataOps enables enterprise data teams to generate significant business value from their data. Testing and Data Observability. Reflow — A system for incremental data processing in the cloud.

Testing 300

Testing Machine Learning Consulting Data Quality 300

DataKitchen

JULY 27, 2023

The Ten Standard Tools To Develop Data Pipelines In Microsoft Azure. While working in Azure with our customers, we have noticed several standard Azure tools people use to develop data pipelines and ETL or ELT processes. We counted ten ‘standard’ ways to transform and set up batch data pipelines in Microsoft Azure.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

datapine

NOVEMBER 11, 2021

a) Data Connectors Features. For a few years now, Business Intelligence (BI) has helped companies to collect, analyze, monitor, and present their data in an efficient way to extract actionable insights that will ensure sustainable growth. Your Chance: Want to take your data analysis to the next level? Table of Contents.

Business Intelligence 213

Business Intelligence Dashboards Interactive Visualization 213

Ontotext

FEBRUARY 26, 2024

The goal: a data-driven organization Let’s zoom out for a bit. Every organization wants to be data-driven. The goal is to capture data, convert it into the right insights, and integrate those insights quickly and efficiently into your business decisions and processes. And this includes the AI space.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

CDW Research Hub

NOVEMBER 17, 2021

Before big data and the cloud, it wasn’t a big deal for organizations to create and manage their own data. So, how can organizations get back in the driver’s seat when it comes to their data? Here are five ways you can simplify data management and stop data silos in their tracks. Prioritize data protection.

Strategy 83

Strategy Data Governance Data Warehouse Data-driven 83

erwin

FEBRUARY 19, 2021

Metadata management is key to wringing all the value possible from data assets. However, most organizations don’t use all the data at their disposal to reach deeper conclusions about how to drive revenue, achieve regulatory compliance or accomplish other strategic objectives. Quite simply, metadata is data about data.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

IBM Big Data Hub

OCTOBER 12, 2023

Connecting AI models to a myriad of data sources across cloud and on-premises environments AI models rely on vast amounts of data for training. Once trained and deployed, models also need reliable access to historical and real-time data to generate content, make recommendations, detect errors, send proactive alerts, etc.

Cost-Benefit 83

Cost-Benefit Metadata Data Governance Modeling 83

Alation

JANUARY 25, 2022

Data fabric is now on the minds of most data management leaders. In our previous blog, Data Mesh vs. Data Fabric: A Love Story , we defined data fabric and outlined its uses and motivations. The data catalog is a foundational layer of the data fabric.

Metadata 52

Metadata IT Metrics Data-driven 52

Sisense

JULY 22, 2020

We live in a world of data: there’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways organizations tackle the challenges of this new world to help their companies and their customers thrive. Understanding how data becomes insights.

Slice and Dice 98

Slice and Dice Digital Transformation Data Warehouse Data Lake 98

Cloudera

SEPTEMBER 12, 2022

It sounds straightforward: you just need data and the means to analyze it. The data is there, in spades. Data volumes have been growing for years and are predicted to reach 175 ZB by 2025. First, organizations have a tough time getting their arms around their data. Unified data fabric. Yes and no.

Unstructured Data 72

Unstructured Data Data Architecture Data Lake Snapshot 72