AWS Big Data

JUNE 6, 2023

Data consumers lose trust in data if it isn’t accurate and recent, making data quality essential for undertaking optimal and correct decisions. Evaluation of the accuracy and freshness of data is a common task for engineers. Currently, various tools are available to evaluate data quality.

Data Quality 98

Data Quality Data-driven Data Lake Metrics 98

datapine

SEPTEMBER 27, 2022

Our next book is dedicated to anyone who wants to start a career as a data scientist and is looking to get all the knowledge and skills in a way that is accessible and well-structured. Originally published in 2018, the book has a second edition that was released in January of 2022. 4) “SQL Performance Explained” by Markus Winand.

Business Intelligence 292

Business Intelligence Data Warehouse Data Processing Data mining 292

AWS Big Data

JUNE 6, 2023

Poor-quality data can lead to incorrect insights, bad decisions, and lost opportunities. AWS Glue Data Quality measures and monitors the quality of your dataset. It supports both data quality at rest and data quality in AWS Glue extract, transform, and load (ETL) pipelines.

Data Quality 95

Data Quality Data Lake Visualization Data-driven 95

AWS Big Data

SEPTEMBER 11, 2024

This also includes building an industry standard integrated data repository as a single source of truth, operational reporting through real time metrics, data quality monitoring, 24/7 helpdesk, and revenue forecasting through financial projections and supply availability projections.

Data Architecture 111

Data Architecture Optimization Data Warehouse Metadata 111

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. This makes sure the new data platform can meet current and future business goals.

Data Warehouse 115

Data Warehouse KPI Optimization Cost-Benefit 115

AWS Big Data

DECEMBER 4, 2024

With this new functionality, customers can create up-to-date replicas of their data from applications such as Salesforce, ServiceNow, and Zendesk in an Amazon SageMaker Lakehouse and Amazon Redshift. SageMaker Lakehouse gives you the flexibility to access and query your data in-place with all Apache Iceberg compatible tools and engines.

Data Integration 114

Data Integration Data Lake Statistics Data-driven 114

AWS Big Data

MAY 7, 2024

It also makes it easier for engineers, data scientists, product managers, analysts, and business users to access data throughout an organization to discover, use, and collaborate to derive data-driven insights. The producer also needs to manage and publish the data asset so it’s discoverable throughout the organization.

Metadata 107

Metadata Data Lake Data Processing Data-driven 107

Smart Data Collective

OCTOBER 13, 2021

Data virtualization is ideal in any situation where the is necessary: Information coming from diverse data sources. Multi-channel publishing of data services. How does Data Virtualization manage data quality requirements? How does Data Virtualization complement Data Warehousing and SOA Architectures?

Visualization 145

Visualization Cost-Benefit Big Data Prescriptive Analytics 145

AWS Big Data

MARCH 7, 2023

Data lakes are more focused around storing and maintaining all the data in an organization in one place. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.

Analytics 96

Analytics Data Warehouse Data Lake Metadata 96

AWS Big Data

JULY 25, 2024

Solution To address the challenge, ATPCO sought inspiration from a modern data mesh architecture. In Amazon DataZone, data owners can publish their data and its business catalog (metadata) to ATPCO’s DataZone domain. Data consumers can then search for relevant data assets using these human-friendly metadata terms.

Data Lake 115

Data Lake Metadata Sales Publishing 115

AWS Big Data

APRIL 4, 2024

Griffin is an open source data quality solution for big data, which supports both batch and streaming mode. In today’s data-driven landscape, where organizations deal with petabytes of data, the need for automated data validation frameworks has become increasingly critical.

Data Quality 86

Data Quality Data Lake Data Warehouse Data-driven 86

IBM Big Data Hub

APRIL 27, 2022

Since its uniquely metadata-driven, the abstraction layer of a data fabric makes it easier to model, integrate and query any data sources, build data pipelines, and integrate data in real-time. This improves data engineering productivity and time-to-value for data consumers. What’s a data mesh?

Management 79

Management Metadata Data Architecture Data Lake 79

AWS Big Data

DECEMBER 9, 2024

Given the importance of data in the world today, organizations face the dual challenges of managing large-scale, continuously incoming data while vetting its quality and reliability. AWS Glue is a serverless data integration service that you can use to effectively monitor and manage data quality through AWS Glue Data Quality.

Data Quality 125

Data Quality Publishing Snapshot Data Lake 125

CIO Business Intelligence

NOVEMBER 29, 2022

Layering technology on the overall data architecture introduces more complexity. Today, data architecture challenges and integration complexity impact the speed of innovation, data quality, data security, data governance, and just about anything important around generating value from data.

Data Architecture 111

Data Architecture Data Integration IoT Data-driven 111

AWS Big Data

JANUARY 31, 2023

Data governance is increasingly top-of-mind for customers as they recognize data as one of their most important assets. Effective data governance enables better decision-making by improving data quality, reducing data management costs, and ensuring secure access to data for stakeholders.

Data Lake 98

Data Lake Data Governance Data Architecture Machine Learning 98

Cloudera

SEPTEMBER 9, 2022

This is the promise of the modern data lakehouse architecture. analyst Sumit Pal, in “Exploring Lakehouse Architecture and Use Cases,” published January 11, 2022: “Data lakehouses integrate and unify the capabilities of data warehouses and data lakes, aiming to support AI, BI, ML, and data engineering on a single platform.”

Metadata 102

Metadata Machine Learning Unstructured Data Data Lake 102

Andrew White

DECEMBER 4, 2019

If I am moved to write research about a vendor, I’ll write it and publish it behind our pay wall, in the assumption the advice is valuable. If you read my blog regularly then you know I rarely write about IT vendors. No single application vendor solves single source of truth since, by their own definition, they sell multiple applications.

Digital Transformation 64

Digital Transformation Data Quality Data Integration Data Warehouse 64

Ontotext

FEBRUARY 12, 2024

It proposes a technological, architectural, and organizational approach to solving data management problems by breaking up the monolithic data platform and de-centralizing data management across different domain teams and services. Some examples of data products are data sets, tables, machine learning models, and APIs.

IT 64

IT Metadata Data Quality Data Lake 64

CIO Business Intelligence

FEBRUARY 14, 2023

It’s clear how these real-time data sources generate data streams that need new data and ML models for accurate decisions. Data quality is crucial for real-time actions because decisions often can’t be taken back.

Data Strategy 116

Data Strategy Strategy Machine Learning Data-driven 116

Jet Global

FEBRUARY 25, 2025

Data cleansing is the process of identifying and correcting errors, inconsistencies, and inaccuracies in a dataset to ensure its quality, accuracy, and reliability. This process is crucial for businesses that rely on data-driven decision-making, as poor data quality can lead to costly mistakes and inefficiencies.

Cost-Benefit 52

Cost-Benefit Data Collection Finance Reporting 52

Alation

JUNE 30, 2022

And as new technology allowed for more publishers and created a higher volume of content, information curation thrived. In today’s data-driven world, many data workers are struggling with high volumes of often redundant data… and many long for a data user’s version of Wikipedia. Data quality can change with time.

Metadata 52

Metadata Data Warehouse Data Quality Data-driven 52

Howard Dresner

JANUARY 4, 2015

He has published two books on the subject, The Performance Management Revolution — Business Results through Insight and Action, and Profiles in Performance — Business Intelligence Journeys and the Roadmap for Change.

Business Intelligence 45

Business Intelligence Recreation/Entertainment Sales Data Quality 45

Ontotext

NOVEMBER 16, 2023

Data mesh solves this by promoting data autonomy, allowing users to make decisions about domains without a centralized gatekeeper. It also improves development velocity with better data governance and access with improved data quality aligned with business needs.

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

AWS Big Data

MARCH 3, 2023

It has been well published since the State of DevOps 2019 DORA Metrics were published that with DevOps, companies can deploy software 208 times more often and 106 times faster, recover from incidents 2,604 times faster, and release 7 times fewer defects. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

Smarten

NOVEMBER 26, 2023

You may be interested to know that TechJury reports seven out of ten businesses rate data discovery as very important, and that the top three business intelligence trends are data visualization, data quality management and self-service business intelligence.

Marketing 40

Marketing Business Intelligence Key Performance Indicator Prescriptive Analytics 40

Alation

JANUARY 26, 2023

Offer the right tools Data stewardship is greatly simplified when the right tools are on hand. So ask yourself, does your steward have the software to spot issues with data quality, for example? 2) Always Remember Compliance Source: Unsplash There are now many different data privacy and security laws worldwide.

Data Governance 52

Data Governance Strategy Data Quality Data Collection 52

Andrew White

JANUARY 11, 2021

This was for the Chief Data Officer, or head of data and analytics. Gartner also published the same piece of research for other roles, such as Application and Software Engineering. See recorded webinars: Emerging Practices for a Data-driven Strategy. Link Data to Business Outcomes. Very interesting.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Domino Data Lab

JULY 22, 2019

The data governance, however, is still pretty much over on the data warehouse. Toward the end of the 2000s is when you first started getting teams and industry, as Josh Willis was showing really brilliantly last night, you first started getting some teams identified as “data science” teams. You know what?

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Domino Data Lab

FEBRUARY 4, 2019

In other words, your talk didn’t quite stand out enough to put onstage, but you still get “publish or perish” credits for presenting. That approach probably created data silos between divisions, due to costs, budgets, accounting procedures, etc. A free mini-book about the second survey, Evolving Data Infrastructure, just published.

Data Science 66

Data Science Experimentation Machine Learning Data-driven 66

Jet Global

DECEMBER 23, 2021

Data quality has always been at the heart of financial reporting , but with rampant growth in data volumes, more complex reporting requirements and increasingly diverse data sources, there is a palpable sense that some data, may be eluding everyday data governance and control. Data Quality Audit.

Data Quality 98

Data Quality Reporting Recreation/Entertainment Finance 98

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Jet Global

JANUARY 30, 2025

Preventing Data Swamps: Best Practices for Clean Data Preventing data swamps is crucial to preserving the value and usability of data lakes, as unmanaged data can quickly become chaotic and undermine decision-making.

Data Lake 64

Data Lake Data-driven Optimization Enterprise 64

Jet Global

FEBRUARY 23, 2024

The quick and dirty definition of data mapping is the process of connecting different types of data from various data sources. Data mapping is a crucial step in data modeling and can help organizations achieve their business goals by enabling data integration, migration, transformation, and quality.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Visualization 52

Jet Global

FEBRUARY 21, 2025

This trend, coupled with evolving work patterns like remote work and the gig economy, has significantly impacted traditional talent acquisition and retention strategies, making it increasingly challenging to find and retain qualified finance talent.

Finance 52

Finance Reporting Forecasting Software 52

datapine

AUGUST 29, 2022

Due to this book being published recently, there are not any written reviews available. 4) Big Data: Principles and Best Practices Of Scalable Real-Time Data Systems by Nathan Marz and James Warren. Best for: the seasoned BI professional who is ready to think deep and hard about important issues in data analytics and big data.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Jet Global

FEBRUARY 23, 2024

A Centralized Hub for Data Data silos are the number one inhibitor to commerce success regardless of your business model. Through effective workflow, data quality, and governance tools, a PIM ensures that disparate content is transformed into a company-wide strategic asset. Publish with Ease Publishing from a PIM is easy.

Management 52

Management Sales Publishing Data Quality 52

Jet Global

OCTOBER 26, 2023

If your finance team is using JD Edwards (JDE) and Oracle E-Business Suite (EBS), it’s like they rely on well-maintained and accurate master data to drive meaningful insights through reporting. For these teams, data quality is critical. Ensuring that data is integrated seamlessly for reporting purposes can be a daunting task.

Data Quality 52

Data Quality Reporting Operational Reporting Finance 52