AWS Big Data

DECEMBER 4, 2024

Ask questions in plain English to find the right datasets, automatically generate SQL queries, or create data pipelines without writing code. With this launch, you can query data regardless of where it is stored with support for a wide range of use cases, including analytics, ad-hoc querying, data science, machine learning, and generative AI.

Data Analytics 91

Data Analytics Analytics Data Lake Data Quality 91

TDAN

DECEMBER 4, 2024

We have lots of data conferences here. I’ve taken to asking a question at these conferences: What does data quality mean for unstructured data? Over the years, I’ve seen a trend — more and more emphasis on AI. This is my version of […]

Unstructured Data 52

Unstructured Data Data Quality Data Architecture Modeling 52

Cloudera

MARCH 28, 2024

But, even with the backdrop of an AI-dominated future, many organizations still find themselves struggling with everything from managing data volumes and complexity to security concerns to rapidly proliferating data silos and governance challenges. Let’s explore some of the most important findings that the survey uncovered.

Data Architecture 94

Data Architecture Strategy Data Lake Data-driven 94

CIO Business Intelligence

MARCH 24, 2023

It encompasses the people, processes, and technologies required to manage and protect data assets. The Data Management Association (DAMA) International defines it as the “planning, oversight, and control over management of data and the use of data and data-related sources.”

Data Governance 142

Data Governance Management Metadata Data Quality 142

AWS Big Data

JUNE 6, 2023

AWS Glue Data Quality allows you to measure and monitor the quality of data in your data repositories. It’s important for business users to be able to see quality scores and metrics to make confident business decisions and debug data quality issues. An AWS Glue crawler crawls the results.

Data Quality 84

Data Quality Metrics Visualization Dashboards 84

Cloudera

SEPTEMBER 6, 2022

There remain challenges in workforce management, particularly in call centers, and order backlogs for fiber broadband and other physical infrastructure are being worked through. Why telco should consider modern data architecture. What is the rationale for driving a modern data architecture? The challenges.

Data Architecture 84

Data Architecture Cost-Benefit Digital Transformation Business Driver 84

AWS Big Data

SEPTEMBER 11, 2024

Their large inventory requires extensive supply chain management to source parts, make products, and distribute them globally. This complex process involves suppliers, logistics, quality control, and delivery. The data quality (DQ) checks are managed using DQ configurations stored in Aurora PostgreSQL tables.

Data Architecture 101

Data Architecture Optimization Data Warehouse Metadata 101

AWS Big Data

OCTOBER 9, 2024

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. This takes away important person hours from the actual migration effort into building and maintaining a data parity framework.

Data Quality 101

Data Quality Data Lake Data Warehouse Metrics 101

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 107

Data Quality Data Governance Data Lake Testing 107

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). Manage policies and rules. Govern PII “in motion”.

Data Governance 110

Data Governance Management Metadata Risk Management 110

erwin

OCTOBER 24, 2019

In fact, data professionals spend 80 percent of their time looking for and preparing data and only 20 percent of their time on analysis , according to IDC. To flip this 80/20 rule, they need an automated metadata management solution for: • Discovering data – Identify and interrogate metadata from various data management silos.

Metadata 104

Metadata Management Data-driven Data Architecture 104

Cloudera

AUGUST 30, 2022

That should be easy, but when agencies don’t share data or applications, they don’t have a unified view of people. As such, managers at different agencies need to sort through multiple systems to make sure these documents are delivered correctly—even though they all apply to the same individuals.”. Modern data architectures.

Data Architecture 79

Data Architecture Data Lake Data Warehouse Metadata 79

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. For many organizations, the real challenge is quantifying the ROI benefits of data management in terms of dollars and cents.

Strategy 116

Strategy Management Key Performance Indicator Cost-Benefit 116

AWS Big Data

NOVEMBER 22, 2024

This integration enables data teams to efficiently transform and manage data using Athena with dbt Cloud’s robust features, enhancing the overall data workflow experience. This enables you to extract insights from your data without the complexity of managing infrastructure.

Data Lake 89

Data Lake Data Warehouse Cost-Benefit Data Transformation 89

Smart Data Collective

FEBRUARY 23, 2021

When you collect data about your audience and campaigns, you’ll be better placed to understand what works for them and what doesn’t. So, what can happen if you end up committing big data mistakes ? If you don’t manage your big data well, the mistakes may end up giving you incorrect insights. Ignoring Data Quality.

Big Data 142

Big Data Visualization Data Quality Data-driven 142

AWS Big Data

JANUARY 15, 2025

Their terminal operations rely heavily on seamless data flows and the management of vast volumes of data. With the addition of these technologies alongside existing systems like terminal operating systems (TOS) and SAP, the number of data producers has grown substantially.

IoT 105

IoT Machine Learning Metadata Data-driven 105

CIO Business Intelligence

JULY 28, 2023

Enterprises are dealing with increasing amounts of data, and managing it has become imperative to optimize its value and keep it secure. Data lifecycle management is essential to ensure it is managed effectively from creation, storage, use, sharing, and archive to the end of life when it is deleted.

Risk 98

Risk Management Data mining Cost-Benefit 98

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

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

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. What is zero-ETL?

Data Integration 103

Data Integration Data Lake Statistics Data-driven 103

Cloudera

MAY 14, 2024

To attain that level of data quality, a majority of business and IT leaders have opted to take a hybrid approach to data management, moving data between cloud, on-premises -or a combination of the two – to where they can best use it for analytics or feeding AI models. What do we mean by ‘true’ hybrid?

Data Architecture 99

Data Architecture Data Governance Unstructured Data Structured Data 99

CIO Business Intelligence

MARCH 9, 2022

Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure. They’re comparatively expensive and can’t handle big data analytics. However, they do contain effective data management, organization, and integrity capabilities. Pulling it all together.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Big Data 119

erwin

DECEMBER 6, 2019

While many organizations are aware of the need to implement a formal data governance initiative, many have faced obstacles getting started. Creating a Culture of Data Governance. Team Resources : Most successful organizations have established a formal data management group at the enterprise level. Data Security.

Data Governance 145

Data Governance Metadata Enterprise Data-driven 145

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 and cloud strategy must align.

Data Architecture 111

Data Architecture Data Integration IoT Data-driven 111

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 delays impact delivery of the reports to senior management, who are responsible for making business decisions based on the dashboard. A DataOps implementation project consists of three steps.

Testing 152

Testing Metadata Dashboards Statistics 152

Octopai

APRIL 19, 2021

Aptly named, metadata management is the process in which BI and Analytics teams manage metadata, which is the data that describes other data. In other words, data is the context and metadata is the content. Without metadata, BI teams are unable to understand the data’s full story. Donna Burbank.

Metadata 59

Metadata Management Business Intelligence Data Governance 59

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

CIO Business Intelligence

MAY 20, 2022

Modernizing a utility’s data architecture. These capabilities allow us to reduce business risk as we move off of our monolithic, on-premise environments and provide cloud resiliency and scale,” the CIO says, noting National Grid also has a major data center consolidation under way as it moves more data to the cloud.

IT 105

IT Internet of Things Digital Transformation Data Architecture 105

AWS Big Data

AUGUST 1, 2024

Large-scale data warehouse migration to the cloud is a complex and challenging endeavor that many organizations undertake to modernize their data infrastructure, enhance data management capabilities, and unlock new business opportunities.

Data Warehouse 105

Data Warehouse KPI Optimization Cost-Benefit 105

CIO Business Intelligence

AUGUST 9, 2022

These include: Generalist: Data engineers who typically work for small teams or small companies wear many hats as one of the few “data-focused” people in the company. These generalists are often responsible for every step of the data process, from managing data to analyzing it. Data engineer job description.

Analytics 131

Analytics Data Science Statistics Unstructured Data 131

erwin

DECEMBER 12, 2019

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. Managing metadata should not be a sub-goal of data governance. As data continues to proliferate, so does the need for data and analytics initiatives to make sense of it all.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

AWS Big Data

NOVEMBER 9, 2023

It allows users to write data transformation code, run it, and test the output, all within the framework it provides. dbt enables you to write SQL select statements, and then it manages turning these select statements into tables or views in Amazon Redshift. It’s raw, unprocessed data straight from the source.

Data Warehouse 122

Data Warehouse Testing Data Quality Reporting 122

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 Unstructured Data 52

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 96

Data Lake Analytics Snapshot Data Quality 96

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. Improved Customer and Employee Satisfaction.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

CIO Business Intelligence

JANUARY 30, 2024

“CIOs are in a unique position to drive data availability at scale for ESG reporting as they understand what is needed and why, and how it can be done.” “The As regulation emerges, the needs for auditable, data-backed reporting is raising the stakes and elevating the role of data in ESG — and hence the [role of the] CIO.”

Reporting 115

Reporting Data Quality Strategy Data-driven 115

CIO Business Intelligence

JUNE 23, 2023

CIOs should prioritize an adaptable technology infrastructure that eliminates data silos, ensures security and governance, and embraces a unified horizontal platform for streamlined data management, reducing integration complexities, skilled workforce requirements, and costs. Data Center Management, IT Strategy

Data Strategy 116

Data Strategy Strategy Visualization Consulting 116