Alation

MAY 24, 2022

generally available on May 24, Alation introduces the Open Data Quality Initiative for the modern data stack, giving customers the freedom to choose the data quality vendor that’s best for them with the added confidence that those tools will integrate seamlessly with Alation’s Data Catalog and Data Governance application.

Data Quality 98

Data Quality Data Governance Metadata Metrics 98

Jet Global

MAY 28, 2019

Whether the reporting is being done by an end user, a data science team, or an AI algorithm, the future of your business depends on your ability to use data to drive better quality for your customers at a lower cost. So, when it comes to collecting, storing, and analyzing data, what is the right choice for your enterprise?

Data Warehouse 85

Data Warehouse Reporting Business Intelligence Sales 85

CIO Business Intelligence

DECEMBER 11, 2024

To succeed in todays landscape, every company small, mid-sized or large must embrace a data-centric mindset. This article proposes a methodology for organizations to implement a modern data management function that can be tailored to meet their unique needs. Implementing ML capabilities can help find the right thresholds.

Management 111

Management Data Governance Data Science Reporting 111

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 76

Data Quality Data Lake Visualization Data-driven 76

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. 4) How can you ensure data quality? Who are they?

IT 317

IT Statistics KPI Data-driven 317

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 83

Data Quality Data-driven Data Lake Metrics 83

datapine

SEPTEMBER 27, 2022

Here is an excerpt from one: “I use SQL daily, and this was a great reference towards using advanced SQL to get analytics insights. It’s something you should have on your desk for reference at all times and the best book on SQL if you want to step outside the box while fine-tuning your technical skills. Viescas, Douglas J.

Business Intelligence 292

Business Intelligence Data Warehouse Data Processing Data mining 292

DataKitchen

SEPTEMBER 21, 2023

What is Data in Place? Data in Place refers to the organized structuring and storage of data within a specific storage medium, be it a database, bucket store, files, or other storage platforms. There are multiple locations where problems can happen in a data and analytic system. What is Data in Use?

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

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 110

Data Governance Unstructured Data Metadata Data Lake 110

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 100

Data Warehouse KPI Optimization Cost-Benefit 100

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 82

Data Warehouse Cost-Benefit Metadata Data-driven 82

BI-Survey

FEBRUARY 17, 2020

From operational systems to support “smart processes”, to the data warehouse for enterprise management, to exploring new use cases through advanced analytics : all of these environments incorporate disparate systems, each containing data fragments optimized for their own specific task. .

Data Governance 89

Data Governance Data Warehouse Data Quality Data Strategy 89

Smart Data Collective

APRIL 29, 2020

What is data management? Data management can be defined in many ways. Usually the term refers to the practices, techniques and tools that allow access and delivery through different fields and data structures in an organisation. Data transformation. Data analytics and visualisation. Microsoft Azure.

Management 98

Management Data Warehouse Digital Transformation Dashboards 98

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 97

Data Architecture Optimization Data Warehouse Metadata 97

CIO Business Intelligence

MARCH 22, 2022

One option is a data lake—on-premises or in the cloud—that stores unprocessed data in any type of format, structured or unstructured, and can be queried in aggregate. Another option is a data warehouse, which stores processed and refined data. Ready to evolve your analytics strategy or improve your data quality?

Analytics 115

Analytics Key Performance Indicator Data Warehouse Data-driven 115

AWS Big Data

MARCH 7, 2023

Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. 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 79

Analytics Data Warehouse Data Lake Metadata 79

erwin

JULY 17, 2019

Outsourcing these data management efforts to professional services firms only delays schedules and increases costs. With automation, data quality is systemically assured. The data pipeline is seamlessly governed and operationalized to the benefit of all stakeholders. Digital Transformation Strategy: Smarter Data.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

datapine

FEBRUARY 22, 2022

A business intelligence strategy refers to the process of implementing a BI system in your company. This should also include creating a plan for data storage services. Are the data sources going to remain disparate? Or does building a data warehouse make sense for your organization? Define a budget.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Dashboards 218

Cloudera

AUGUST 26, 2020

Gluent’s Smart Connector is capable of pushing processing to Cloudera, thereby reducing the storage and compute footprint on traditional data warehouses like Oracle. This allows our customers to reduce spend on highly specialized hardware and leverage the tools of a modern data warehouse. . Certified Data Quality Partner.

Machine Learning 84

Machine Learning Big Data Data Warehouse Data-driven 84

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 98

Data Integration Data Lake Statistics Data-driven 98

AWS Big Data

FEBRUARY 13, 2023

We live in a data-producing world, and as companies want to become data driven, there is the need to analyze more and more data. These analyses are often done using data warehouses. Status quo before migration Here at OLX Group, Amazon Redshift has been our choice for data warehouse for over 5 years.

Snapshot 73

Snapshot Data Warehouse Analytics Testing 73

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 97

Enterprise Data Warehouse Snapshot Cost-Benefit 97

erwin

FEBRUARY 28, 2019

The smart cities movement refers to the broad effort of municipal governments to incorporate sensors, data collection and analysis to improve responses to everything from rush-hour traffic to air quality to crime prevention. Data governance doesn’t take place at a single application or in the data warehouse.

Digital Transformation 106

Digital Transformation Data Governance Data-driven Data Warehouse 106

AWS Big Data

FEBRUARY 8, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Amazon Redshift enables you to run complex SQL analytics at scale and performance on terabytes to petabytes of structured and unstructured data, and make the insights widely available through popular business intelligence (BI) and analytics tools.

Data Quality 84

Data Quality Testing Data Warehouse Unstructured Data 84

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. Basic formatting and readability of the data is standardized here.

Optimization 96

Optimization B2B Data Quality Sales 96

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 90

Data Lake Data Governance Data Architecture Machine Learning 90

Wayne Yaddow

MARCH 12, 2025

However, Great Expectations (GX ) sets itself apart as a robust, open-source framework that helps data teams maintain consistent and transparent data quality standards. Data quality rules are codified into structured Expectation Suites by Great Expectations instead of relying on ad-hoc scripts or manual checks.

Data Transformation 52

Data Transformation Data Quality Testing Data Warehouse 52

Cloudera

APRIL 14, 2021

Refer to the following cloudera blog to understand the full potential of Cloudera Data Engineering. . Precisely Data Integration, Change Data Capture and Data Quality tools support CDP Public Cloud as well as CDP Private Cloud. For further details on the API, please refer to the following doc link here. .

Data Warehouse 84

Data Warehouse Data Processing Machine Learning Data Quality 84

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. For setup instructions, refer to Getting started with Amazon OpenSearch Service.

Analytics 108

Analytics IT Data Lake Visualization 108

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 78

Data Strategy Strategy Data Warehouse Prescriptive Analytics 78

Jet Global

MAY 1, 2020

Because, admit it—you’ve done it, we’ve done it, too—you extract data from an internal system, and you load it into Excel, and then you manipulate the numbers. The danger here is obvious: Each and every person who does this is going to have a different frame of reference. The mechanical solution is to build a data warehouse.

Data Warehouse 64

Data Warehouse Data Quality Risk Reporting 64

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. If you’d like to learn more about other workflows in this solution, please refer to the implementation guide.

Metadata 87

Metadata Data Lake Data Processing Data-driven 87

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. It helps in determining what data you have and its sensitivity. However, it’s not without its challenges.

Data-driven 119

Data-driven Machine Learning Risk Deep Learning 119

Cloudera

SEPTEMBER 15, 2022

Mark: The first element in the process is the link between the source data and the entry point into the data platform. At Ramsey International (RI), we refer to that layer in the architecture as the foundation, but others call it a staging area, raw zone, or even a source data lake. What is a data fabric?

Data Lake 83

Data Lake Data Architecture Data-driven Data Warehouse 83

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 71

Data Quality Data Lake Data Warehouse Data-driven 71

Octopai

FEBRUARY 12, 2020

There’s a distinction between a data dictionary and a business glossary. A data dictionary is a tool that organizes and describes different variables indicated by metadata associated with a dataset. A business glossary, sometimes referred to as a data glossary , is a broader tool.

Metadata 72

Metadata Enterprise Management Data Warehouse 72

Jedox

JANUARY 7, 2021

The terms supply chain management or supply chain planning are also often used when referring to the process of sales and operations planning. While many organizations already use some form of planning software, they’re often challenged by fragmented systems resulting in data silos and, therefore, inconsistent data.

Sales 81

Sales Forecasting Data Warehouse Finance 81