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 Architecture 52

Data Architecture Data Quality Strategy Data Lake 52

AWS Big Data

OCTOBER 9, 2024

Data parity can help build confidence and trust with business users on the quality of migrated data. Some customers build custom in-house data parity frameworks to validate data during migration. Others use open source data quality products for data parity use cases.

Data Quality 112

Data Quality Data Lake Data Warehouse Metrics 112

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. Second-generation – gigantic, complex data lake maintained by a specialized team drowning in technical debt. Introduction to Data Mesh. See the pattern?

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

Cloudera

MARCH 28, 2024

At a time when AI is exploding in popularity and finding its way into nearly every facet of business operations, data has arguably never been more valuable. As organizations continue to navigate this AI-driven world, we set out to understand the strategies and emerging data architectures that are defining the future.

Data Architecture 94

Data Architecture Strategy Data Lake Data-driven 94

Cloudera

SEPTEMBER 6, 2022

Data has continued to grow both in scale and in importance through this period, and today telecommunications companies are increasingly seeing data architecture as an independent organizational challenge, not merely an item on an IT checklist. Previously, there were three types of data structures in telco: .

Data Architecture 84

Data Architecture Cost-Benefit Digital Transformation Business Driver 84

AWS Big Data

OCTOBER 10, 2023

Data governance is the process of ensuring the integrity, availability, usability, and security of an organization’s data. Due to the volume, velocity, and variety of data being ingested in data lakes, it can get challenging to develop and maintain policies and procedures to ensure data governance at scale for your data lake.

Data Quality 109

Data Quality Data Governance Data Lake Testing 109

AWS Big Data

SEPTEMBER 11, 2024

This post describes how HPE Aruba automated their Supply Chain management pipeline, and re-architected and deployed their data solution by adopting a modern data architecture on AWS. The data quality (DQ) checks are managed using DQ configurations stored in Aurora PostgreSQL tables.

Data Architecture 109

Data Architecture Optimization Data Warehouse Metadata 109

Cloudera

JUNE 29, 2023

To improve the way they model and manage risk, institutions must modernize their data management and data governance practices. Implementing a modern data architecture makes it possible for financial institutions to break down legacy data silos, simplifying data management, governance, and integration — and driving down costs.

Data Architecture 85

Data Architecture Risk Management Risk Management 85

CIO Business Intelligence

APRIL 24, 2025

Clear path to the cloud The second focus area is modernizing the companys basic platform and moving everything to the cloud and adapting the architecture accordingly. It also enables other types of efficiency improvements, such as building good conditions for a data platform, which is a prerequisite for using new technology like AI.

IT 72

IT Consulting Optimization IoT 72

Cloudera

AUGUST 30, 2022

But while state and local governments seek to improve policies, decision making, and the services constituents rely upon, data silos create accessibility and sharing challenges that hinder public sector agencies from transforming their data into a strategic asset and leveraging it for the common good. . Modern data architectures.

Data Architecture 79

Data Architecture Data Lake Data Warehouse Metadata 79

Jim Harris

JANUARY 1, 2016

1 — Investigate Data quality is not exactly a riddle wrapped in a mystery inside an enigma. However, understanding your data is essential to using it effectively and improving its quality. In order for you to make sense of those data elements, you require business context.

Data Quality 61

Data Quality Data Governance Cost-Benefit ROI 61

CIO Business Intelligence

DECEMBER 11, 2024

A similar transformation has occurred with data. More than 20 years ago, data within organizations was like scattered rocks on early Earth. It was not alive because the business knowledge required to turn data into value was confined to individuals minds, Excel sheets or lost in analog signals.

Management 111

Management Data Governance Data Science Reporting 111

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. Determine the changes in transaction, and write new data files. This scenario applies to any type of updates on an Iceberg table.

Snapshot 137

Snapshot Management Metadata Big Data 137

Smart Data Collective

FEBRUARY 23, 2021

Ignoring Data Quality. One of the biggest big data mistakes that you can make as a marketer is that of ignoring the quality of your data. You need to sort your data, tag it well, and even quality control it to ensure that the data points are relevant and accurate. Analyzing Data Without a Goal.

Big Data 142

Big Data Visualization Data Quality Data-driven 142

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 63

Data Quality Data Integration Metadata Cost-Benefit 63

AWS Big Data

NOVEMBER 22, 2024

This enables you to extract insights from your data without the complexity of managing infrastructure. dbt has emerged as a leading framework, allowing data teams to transform and manage data pipelines effectively. With dbt, teams can define data quality checks and access controls as part of their transformation workflow.

Data Lake 102

Data Lake Data Warehouse Cost-Benefit Data Transformation 102

CIO Business Intelligence

MAY 20, 2022

Modernizing a utility’s data architecture. The utility is about one third of the way through its cloud transition and is focused on moving customer data and workforce data to the cloud first to reap the most business value. We’re very mature in our data architecture and what we want. National Grid.

IT 105

IT Internet of Things Digital Transformation Data Architecture 105

CIO Business Intelligence

FEBRUARY 28, 2024

So by using the company’s data, a general-purpose language model becomes a useful business tool. And not only do companies have to get all the basics in place to build for analytics and MLOps, but they also need to build new data structures and pipelines specifically for gen AI. They need stability. They’re not great for knowledge.”

IT 131

IT Consulting Modeling Enterprise 131

AWS Big Data

JANUARY 15, 2025

Their terminal operations rely heavily on seamless data flows and the management of vast volumes of data. Recently, EUROGATE has developed a digital twin for its container terminal Hamburg (CTH), generating millions of data points every second from Internet of Things (IoT)devices attached to its container handling equipment (CHE).

IoT 109

IoT Machine Learning Metadata Data-driven 109

CIO Business Intelligence

MARCH 24, 2023

Data governance definition Data governance is a system for defining who within an organization has authority and control over data assets and how those data assets may be used. It encompasses the people, processes, and technologies required to manage and protect data assets.

Data Governance 142

Data Governance Management Metadata Data Quality 142

CIO Business Intelligence

JANUARY 20, 2023

But to get maximum value out of data and analytics, companies need to have a data-driven culture permeating the entire organization, one in which every business unit gets full access to the data it needs in the way it needs it. This is called data democratization. Many platforms are out there,” he says.

Data Lake 135

Data Lake Data-driven Finance Data Architecture 135

IBM Big Data Hub

AUGUST 4, 2023

Data democratization, much like the term digital transformation five years ago, has become a popular buzzword throughout organizations, from IT departments to the C-suite. It’s often described as a way to simply increase data access, but the transition is about far more than that.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

Data Virtualization

FEBRUARY 28, 2020

Too often the design of new data architectures is based on old principles: they are still very data-store-centric. They consist of many physical data stores in which data is stored repeatedly and redundantly. Over time, new types of data stores,

Data Architecture 52

Data Architecture Data Lake Digital Transformation Data Quality 52

AWS Big Data

FEBRUARY 27, 2024

In the ever-evolving world of finance and lending, the need for real-time, reliable, and centralized data has become paramount. Bluestone , a leading financial institution, embarked on a transformative journey to modernize its data infrastructure and transition to a data-driven organization.

Data-driven 109

Data-driven Data Lake Data Quality Data Governance 109

erwin

JULY 12, 2019

In light of recent, high-profile data breaches, it’s past-time we re-examined strategic data governance and its role in managing regulatory requirements. for alleged violations of the European Union’s General Data Protection Regulation (GDPR). Complexity. Govern PII “in motion”. Manage policies and rules.

Data Governance 110

Data Governance Management Metadata Risk Management 110

AWS Big Data

DECEMBER 4, 2024

While traditional extract, transform, and load (ETL) processes have long been a staple of data integration due to its flexibility, for common use cases such as replication and ingestion, they often prove time-consuming, complex, and less adaptable to the fast-changing demands of modern data architectures.

Data Integration 112

Data Integration Data Lake Statistics Data-driven 112

CIO Business Intelligence

MARCH 9, 2022

Applying artificial intelligence (AI) to data analytics for deeper, better insights and automation is a growing enterprise IT priority. But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI. Pulling it all together.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Big Data 119

erwin

OCTOBER 24, 2019

However, most organizations don’t use all the data they’re flooded with to reach deeper conclusions about how to drive revenue, achieve regulatory compliance or make other strategic decisions. They don’t know exactly what data they have or even where some of it is. Metadata Is the Heart of Data Intelligence.

Metadata 104

Metadata Management Data-driven Data Architecture 104

DataKitchen

OCTOBER 11, 2021

First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. The final step is designing a data solution and its implementation. The biggest challenge is broken data pipelines due to highly manual processes. List of Challenges. Definition of Done.

Testing 154

Testing Metadata Dashboards Statistics 154

erwin

DECEMBER 6, 2019

In the data-driven era, CIO’s need a solid understanding of data governance 2.0 … Data governance (DG) is no longer about just compliance or relegated to the confines of IT. Today, data governance needs to be a ubiquitous part of your organization’s culture. It also requires funding.

Data Governance 145

Data Governance Metadata Enterprise Data-driven 145

Cloudera

MAY 14, 2024

But getting there requires data, and a lot of it. More than that, though, harnessing the potential of these technologies requires quality data—without it, the output from an AI implementation can end up inefficient or wholly inaccurate. The challenge is not solved, though, by simply adopting a hybrid cloud infrastructure.

Data Architecture 99

Data Architecture Unstructured Data Data Governance Structured Data 99

TDAN

JUNE 18, 2019

The first step to fixing any problem is to understand that problem—this is a significant point of failure when it comes to data. Most organizations agree that they have data issues, categorized as data quality. However, this definition is […].

Data Quality 90

Data Quality Data Architecture IT Data Governance 90

CIO Business Intelligence

NOVEMBER 29, 2022

A sea of complexity For years, data ecosystems have gotten more complex due to discrete (and not necessarily strategic) data-platform decisions aimed at addressing new projects, use cases, or initiatives. Layering technology on the overall data architecture introduces more complexity.

Data Architecture 111

Data Architecture Data Integration IoT Data-driven 111

CIO Business Intelligence

NOVEMBER 7, 2023

For years, IT and business leaders have been talking about breaking down the data silos that exist within their organizations. In fact, as companies undertake digital transformations , usually the data transformation comes first, and doing so often begins with breaking down data — and political — silos in various corners of the enterprise.

Data Warehouse 142

Data Warehouse Digital Transformation Data-driven Reporting 142

CIO Business Intelligence

JUNE 9, 2023

Such is the case with a data management strategy. That gap is becoming increasingly apparent because of artificial intelligence’s (AI) dependence on effective data management. Leveraging that data, in AI models, for example, depends entirely on the accessibility, quality, granularity, and latency of your organization’s data.

Strategy 116

Strategy Management Key Performance Indicator Cost-Benefit 116

IBM Big Data Hub

APRIL 10, 2023

A well-designed data architecture should support business intelligence and analysis, automation, and AI—all of which can help organizations to quickly seize market opportunities, build customer value, drive major efficiencies, and respond to risks such as supply chain disruptions.

Strategy 85

Strategy Data Architecture Cost-Benefit Reporting 85

erwin

SEPTEMBER 17, 2020

Replace manual and recurring tasks for fast, reliable data lineage and overall data governance. It’s paramount that organizations understand the benefits of automating end-to-end data lineage. The importance of end-to-end data lineage is widely understood and ignoring it is risky business. Doing Data Lineage Right.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143