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. Why telco should consider modern data architecture. The challenges.

Data Architecture 84

Data Architecture Cost-Benefit Digital Transformation Business Driver 84

AWS Big Data

OCTOBER 10, 2023

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 confidentiality and data quality are the two essential themes for data governance.

Data Quality 109

Data Quality Data Governance Data Lake Testing 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

Cloudera

AUGUST 30, 2022

Legacy data sharing involves proliferating copies of data, creating data management, and security challenges. Data quality issues deter trust and hinder accurate analytics. Modern data architectures. Deploying modern data architectures. Forrester ).

Data Architecture 79

Data Architecture Data Lake Data Warehouse Metadata 79

Jim Harris

JANUARY 1, 2016

Lest my pith be misunderstood aplenty, this blog post provides more detail, plus links to related posts, about what I meant. 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.

Data Quality 61

Data Quality Data Governance Cost-Benefit ROI 61

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

Octopai

APRIL 19, 2021

Her Twitter page is filled with interesting articles, webinars, reports, and current news surrounding data management. She tweets and retweets about topics such as data governance, data strategy, and data architecture. TDWI – David Loshin. IRM UK Connects. It is published by Robert S.

Metadata 59

Metadata Management Business Intelligence Data Governance 59

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 113

Data Integration Data Lake Statistics Data-driven 113

IBM Big Data Hub

AUGUST 4, 2023

Today, the way businesses use data is much more fluid; data literate employees use data across hundreds of apps, analyze data for better decision-making, and access data from numerous locations. This results in more marketable AI-driven products and greater accountability.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

Cloudera

MAY 14, 2024

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. Meaningful results, and a scalable, flexible data architecture demand a ‘true’ hybrid cloud approach to data management.

Data Architecture 99

Data Architecture Unstructured Data Data Governance Structured Data 99

erwin

JULY 12, 2019

It also helps enterprises put these strategic capabilities into action by: Understanding their business, technology and data architectures and their inter-relationships, aligning them with their goals and defining the people, processes and technologies required to achieve compliance.

Data Governance 110

Data Governance Management Metadata Risk Management 110

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

OCTOBER 24, 2019

The complexities of metadata management can be addressed with a strong data management strategy coupled with metadata management software to enable the data quality the business requires. Organizations then can take a data-driven approach to business transformation , speed to insights, and risk management.

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. Based on business rules, additional data quality tests check the dimensional model after the ETL job completes. A DataOps implementation project consists of three steps.

Testing 154

Testing Metadata Dashboards Statistics 154

Cloudera

JULY 20, 2021

Invest in maturing and improving your enterprise business metrics and metadata repositories, a multitiered data architecture, continuously improving data quality, and managing data acquisitions. enhanced customer experiences by accelerating the use of data across the organization.

Manufacturing 106

Manufacturing Forecasting IoT Insurance 106

erwin

DECEMBER 6, 2019

Enterprise Data Management Methodology : DG is foundational to enterprise data management. metadata management, enterprise data architecture, data quality management), DG will be a struggle. Without the other essential components (e.g.,

Data Governance 145

Data Governance Metadata Enterprise Data-driven 145

Sisense

AUGUST 28, 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 data teams are tackling the challenges of this new world to help their companies and their customers thrive.

Data Integration 101

Data Integration Testing Data Quality Data-driven 101

Cloudera

DECEMBER 1, 2022

Full-stack observability is a critical requirement for effective modern data platforms to deliver the agile, flexible, and cost-effective environment organizations are looking for. RI is a global leader in the design and deployment of large-scale, production-level modern data platforms for the world’s largest enterprises.

Data Quality 84

Data Quality Metrics Data Lake Statistics 84

Cloudera

SEPTEMBER 15, 2022

The consumption of the data should be supported through an elastic delivery layer that aligns with demand, but also provides the flexibility to present the data in a physical format that aligns with the analytic application, ranging from the more traditional data warehouse view to a graph view in support of relationship analysis.

Data Lake 83

Data Lake Data Architecture Data-driven Data Warehouse 83

Cloudera

JUNE 13, 2024

Cloudera’s true hybrid approach ensures you can leverage any deployment, from virtual private cloud to on-premises data centers, to maximize the use of AI. Reliability – Can you trust that your data quality will yield useful AI results? Responsibility – Can you trust your AI models will give meaningful insight?

Big Data 103

Big Data Machine Learning Contextual Data Data Lake 103

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 79

Management Metadata Data Architecture Data Lake 79

erwin

SEPTEMBER 17, 2020

Here are six benefits of automating end-to-end data lineage: Reduced Errors and Operational Costs. Data quality is crucial to every organization. Automated data capture can significantly reduce errors when compared to manual entry.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. Prior to the creation of the data lake, Orca’s data was distributed among various data silos, each owned by a different team with its own data pipelines and technology stack.

Data Lake 98

Data Lake Analytics Snapshot Data Quality 98

erwin

DECEMBER 12, 2019

As data continues to proliferate, so does the need for data and analytics initiatives to make sense of it all. Quicker Project Delivery: Accelerate Big Data deployments, Data Vaults, data warehouse modernization, cloud migration, etc., by up to 70 percent.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

IBM Big Data Hub

FEBRUARY 9, 2023

In our last blog , we delved into the seven most prevalent data challenges that can be addressed with effective data governance. Today we will share our approach to developing a data governance program to drive data transformation and fuel a data-driven culture. Don’t try to do everything at once!

Data Governance 76

Data Governance Business Objectives Data Quality Measurement 76

Cloudera

JULY 29, 2024

Cloudera’s data-in-motion architecture is a comprehensive set of scalable, modular, re-composable capabilities that help organizations deliver smart automation and real-time data products with maximum efficiency while remaining agile to meet changing business needs.

Enterprise 69

Enterprise Data Architecture Manufacturing Key Performance Indicator 69

Cloudera

OCTOBER 1, 2022

Adam Wood, director of data governance and data quality at a financial services institution (FSI). As countries introduce privacy laws, similar to the European Union’s General Data Protection Regulation (GDPR), the way organizations obtain, store, and use data will be under increasing legal scrutiny.

Data Governance 75

Data Governance Strategy Enterprise Machine Learning 75

erwin

APRIL 16, 2024

One such innovation gaining traction is the data mesh framework. The data mesh approach distributes data ownership and decentralizes data architecture, paving the way for enhanced agility and scalability. Business Glossaries – what is the business meaning of our data?

Metadata 52

Metadata Data Quality Data Governance Data Processing 52

erwin

SEPTEMBER 13, 2022

Learn how to maximize the business impact of your data. Discover how IT, data governance teams, and business users benefit from data intelligence initiatives through automated data cataloging, data quality, data literacy, and self-service data preparation.

Data Governance 52

Data Governance Data-driven Data Architecture Data Quality 52

Sisense

SEPTEMBER 3, 2020

We live in a constantly-evolving world of data. That means that jobs in data big data and data analytics abound. The wide variety of data titles can be dizzying and confusing! Programming and statistics are two fundamental technical skills for data analysts, as well as data wrangling and data visualization.

Statistics 97

Statistics Metrics Visualization Finance 97

BizAcuity

APRIL 14, 2022

Big Data technology in today’s world. Did you know that the big data and business analytics market is valued at $198.08 Or that the US economy loses up to $3 trillion per year due to poor data quality? quintillion bytes of data which means an average person generates over 1.5 megabytes of data every second?

Big Data 52

Big Data Data Analytics Management Analytics 52

Cloudera

SEPTEMBER 7, 2023

The way to manage this is by embedding data integration, data quality-monitoring, and other capabilities into the data platform itself , allowing financial firms to streamline these processes, and freeing them to focus on operationalizing AI solutions while promoting access to data, maintaining data quality, and ensuring compliance.

Insurance 83

Insurance Risk Data-driven Finance 83

IBM Big Data Hub

MAY 15, 2024

Organizations require reliable data for robust AI models and accurate insights, yet the current technology landscape presents unparalleled data quality challenges. Organizations can harness the full potential of their data while reducing risk and lowering costs. However, businesses scaling AI face entry barriers.

Cost-Benefit 67

Cost-Benefit Data Integration Data Architecture Manufacturing 67

IBM Big Data Hub

JANUARY 25, 2023

In our last blog , we introduced Data Governance: what it is and why it is so important. In this blog, we will explore the challenges that organizations face as they start their governance journey. Organizations have long struggled with data management and understanding data in a complex and ever-growing data landscape.

Data Governance 52

Data Governance Data-driven Strategy Data Architecture 52

Ontotext

MAY 30, 2019

And before we move on and look at these three in the context of the techniques Linked Data provides, here is an important reminder in case we are wondering if Linked Data is too good to be true: Linked Data is no silver bullet. 6 Linked Data, Structured Data on the Web. Linked Data and Information Retrieval.

Cost-Benefit 87

Cost-Benefit Big Data Technology Metadata 87

Ontotext

FEBRUARY 12, 2024

This is especially beneficial when teams need to increase data product velocity with trust and data quality, reduce communication costs, and help data solutions align with business objectives. In most enterprises, data is needed and produced by many business units but owned and trusted by no one.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

Alation

NOVEMBER 2, 2022

At Databricks, we’re focused on enabling customers to adopt the data lakehouse, and that’s an open data architecture that combines the best of the data warehouse and the data lake into one platform,” Ferguson says. “[The Subscribe to Alation's Blog. The post Why Invest Now?

Data Governance 98

Data Governance Marketing Finance Data Lake 98