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 70

Data Quality Data Lake Visualization Data-driven 70

David Menninger's Analyst Perspectives

MARCH 17, 2022

Organizations face various challenges with analytics and business intelligence processes, including data curation and modeling across disparate sources and data warehouses, maintaining data quality and ensuring security and governance.

Business Intelligence 204

Business Intelligence Data Warehouse Data Quality Dashboards 204

AWS Big Data

FEBRUARY 29, 2024

First, many LLM use cases rely on enterprise knowledge that needs to be drawn from unstructured data such as documents, transcripts, and images, in addition to structured data from data warehouses. Implement data privacy policies. Implement data quality by data type and source.

Data Governance 99

Data Governance Unstructured Data Metadata Data Lake 99

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 65

Data Quality Data Lake Data Warehouse Data-driven 65

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data Warehouse 81

Data Warehouse Cost-Benefit Metadata Data-driven 81

AWS Big Data

NOVEMBER 9, 2023

The aim was to bolster their analytical capabilities and improve data accessibility while ensuring a quick time to market and high data quality, all with low total cost of ownership (TCO) and no need for additional tools or licenses. dbt emerged as the perfect choice for this transformation within their existing AWS environment.

Data Warehouse 109

Data Warehouse Testing Data Quality Reporting 109

IBM Big Data Hub

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. Ensuring data quality is made easier as a result.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 87

Enterprise Data Warehouse Snapshot Cost-Benefit 87

CIO Business Intelligence

AUGUST 9, 2022

Database-centric: In larger organizations, where managing the flow of data is a full-time job, data engineers focus on analytics databases. Database-centric data engineers work with data warehouses across multiple databases and are responsible for developing table schemas. Data engineer job description.

Analytics 130

Analytics Data Science Statistics Unstructured Data 130

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 73

Analytics Data Warehouse Data Lake Metadata 73

Jet Global

JULY 2, 2019

The sheer scale of data being captured by the modern enterprise has necessitated a monumental shift in how that data is stored. From the humble database through to data warehouses , data stores have grown both in scale and complexity to keep pace with the businesses they serve, and the data analysis now required to remain competitive.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

erwin

FEBRUARY 13, 2020

Other benefits of automating data governance and metadata management processes include: Better Data Quality – Identification and repair of data issues and inconsistencies within integrated data sources in real time.

Metadata 135

Metadata Data Governance Management Cost-Benefit 135

Laminar Security

DECEMBER 13, 2023

They offer a comprehensive solution to enhance your cloud security posture and effectively manage your data. The primary focus of discovery is to find all the places where data exists and identify the assets it resides in. This integration allows for more powerful and sophisticated data discovery and classification processes.

Data-driven 119

Data-driven Machine Learning Risk Deep Learning 119

datapine

JANUARY 24, 2021

This can include a multitude of processes, like data profiling, data quality management, or data cleaning, but we will focus on tips and questions to ask when analyzing data to gain the most cost-effective solution for an effective business strategy. Today, big data is about business disruption.

IT 317

IT Statistics KPI Data-driven 317

AWS Big Data

DECEMBER 21, 2023

As the volume and complexity of analytics workloads continue to grow, customers are looking for more efficient and cost-effective ways to ingest and analyse data. AWS Glue provides both visual and code-based interfaces to make data integration effortless.

Analytics 99

Analytics IT Data Lake Visualization 99

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 77

Data Quality Data Lake Data-driven Metrics 77

erwin

DECEMBER 12, 2019

Here are some benefits of metadata management for data governance use cases: Better Data Quality: Data issues and inconsistencies within integrated data sources or targets are identified in real time to improve overall data quality by increasing time to insights and/or repair. by up to 70 percent.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

erwin

MARCH 8, 2019

Therefore, the organization needed to catalog the data it acquires from suppliers, ensure its quality, classify it, and then sell it to customers. The company wanted to assemble the data in a data warehouse and then provide controlled access to it. This, among other safeguards, ensures data quality.

Data Governance 65

Data Governance Metadata Data Warehouse Data Quality 65

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 84

Data Lake Data Governance Data Architecture Machine Learning 84

IBM Big Data Hub

JUNE 8, 2022

However, a foundational step in evolving into a data-driven organization requires trusted, readily available, and easily accessible data for users within the organization; thus, an effective data governance program is key. Here are a few common data management challenges: Regulatory compliance on data use.

Data-driven 57

Data-driven Enterprise Data Governance Data Lake 57

Octopai

DECEMBER 28, 2022

A data analyst using Power BI doesn’t need to know where the data in her dataset originated. She doesn’t have to identify the source systems, dig into the ETL or rummage through data warehouses. Where is that data quality issue coming from? Your department is considering a change to a business process.

Reporting 52

Reporting Data Quality Visualization Data Warehouse 52

Smart Data Collective

APRIL 29, 2020

The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. This process helps to transform raw data into clean data that can be analysed and aggregated. Data analytics and visualisation. Microsoft Azure.

Management 83

Management Data Warehouse Digital Transformation Dashboards 83

erwin

DECEMBER 12, 2019

Here are some benefits of metadata management for data governance use cases: Better Data Quality: Data issues and inconsistencies within integrated data sources or targets are identified in real time to improve overall data quality by increasing time to insights and/or repair. by up to 70 percent.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

Peter James Thomas

AUGUST 18, 2018

That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. Even back then, these were used for activities such as Analytics , Dashboards , Statistical Modelling , Data Mining and Advanced Visualisation. This is the essence of Convergent Evolution. In Closing.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

Cloudera

MAY 16, 2019

The traditional Data Warehouse ETL process has splintered into many smaller components. Ingest is now focused data capture and real-time trend analysis where possible. Once data is brought under control in a system like Cloudera, then the work of Data Preparation, Quality begins.

Analytics 40

Analytics Data Warehouse Data-driven Data Integration 40

datapine

AUGUST 29, 2022

The saying “knowledge is power” has never been more relevant, thanks to the widespread commercial use of big data and data analytics. The rate at which data is generated has increased exponentially in recent years. Essential Big Data And Data Analytics Insights. million searches per day and 1.2

Big Data 263

Big Data Data Analytics Analytics Data mining 263

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 Big Data Ecosystem.

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

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. report they have established a data culture 26.5%

Data Strategy 115

Data Strategy Strategy Machine Learning Data-driven 115

Alation

FEBRUARY 13, 2020

This brief definition makes several points about data catalogs—data management, searching, data inventory, and data evaluation—but all depend on the central capability to provide a collection of metadata. Data catalogs have become the standard for metadata management in the age of big data and self-service analytics.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

Wise Analytics

SEPTEMBER 30, 2014

The goal of governed data access to support self-service and data discovery applications is to solve data related challenges and support validated data access. This access can be within a centralized data warehouse, through data virtualization, or by accessing approved data sources external to the analytics framework.

Management 40

Management Data Governance Data Warehouse Data Quality 40

AWS Big Data

JUNE 6, 2023

Unless, of course, the rest of their data also resides in the Google Cloud. In this post we showcase how we used AWS Glue to move siloed digital analytics data, with inconsistent arrival times, to AWS S3 (our Data Lake) and our central data warehouse (DWH), Snowflake.

Analytics 56

Analytics Data Lake Testing Optimization 56

DataKitchen

APRIL 13, 2021

Piperr.io — Pre-built data pipelines across enterprise stakeholders, from IT to analytics, tech, data science and LoBs. Prefect Technologies — Open-source data engineering platform that builds, tests, and runs data workflows. Genie — Distributed big data orchestration service by Netflix. Data breaks.

Testing 300

Testing Machine Learning Consulting Data Quality 300

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. Leonardo Gómez is a Principal Big Data / ETL Solutions Architect at AWS, based in Florida, US.

Metadata 78

Metadata Data Lake Data Processing Data-driven 78

CIO Business Intelligence

MARCH 9, 2022

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. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure.

Data Lake 115

Data Lake Unstructured Data Data Warehouse Data Quality 115

Smart Data Collective

JULY 9, 2023

ETL is a three-step process that involves extracting data from various sources, transforming it into a consistent format, and loading it into a target database or data warehouse. Extract The extraction phase involves retrieving data from diverse sources such as databases, spreadsheets, APIs, or other systems.

Data Quality 85

Data Quality Data Warehouse Data-driven Reporting 85

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data.

Data Strategy 71

Data Strategy Strategy Data Warehouse Prescriptive Analytics 71

AWS Big Data

JULY 13, 2023

Data quality for account and customer data – Altron wanted to enable data quality and data governance best practices. Goals – Lay the foundation for a data platform that can be used in the future by internal and external stakeholders.

Optimization 92

Optimization B2B Data Quality Sales 92