Dataversity

SEPTEMBER 24, 2021

We have seen an unprecedented increase in modern data warehouse solutions among enterprises in recent years. Experts believe that this trend will continue: The global data warehousing market is projected to reach $51.18 The reason is pretty obvious – businesses want to leverage the power of data […].

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Dataconomy

MARCH 29, 2025

He suggested that a Feature Store can help manage preprocessed data and facilitate cross-team usage, while a centralized Data Warehouse (DWH) domain can unify data preparation and migration. From the data side, this is resolved through centralized data preparation using a DWH (Data Warehouse) domain, Krotkikh said.

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Data Science Dojo

SEPTEMBER 6, 2023

M aintaining the security and governance of data within a data warehouse is of utmost importance. Data Security: A Multi-layered Approach In data warehousing, data security is not a single barrier but a well-constructed series of layers, each contributing to protecting valuable information.

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Dataversity

DECEMBER 7, 2020

Data warehousing (DW) and business intelligence (BI) projects are a high priority for many organizations who seek to empower more and better data-driven decisions and actions throughout their enterprises. These groups want to expand their user base for data discovery, BI, and analytics so that their business […].

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Data Warehouse Business Intelligence Business Intelligence Analytics 90

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.

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Data Quality Data Governance ETL Data Observability 98

Alation

JULY 28, 2022

It’s costly and time-consuming to manage on-premises data warehouses — and modern cloud data architectures can deliver business agility and innovation. However, CIOs declare that agility, innovation, security, adopting new capabilities, and time to value — never cost — are the top drivers for cloud data warehousing.

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Precisely

MARCH 9, 2023

Data warehouse vs. data lake, each has their own unique advantages and disadvantages; it’s helpful to understand their similarities and differences. In this article, we’ll focus on a data lake vs. data warehouse. Read Many of the preferred platforms for analytics fall into one of these two categories.

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Pickl AI

JUNE 11, 2024

Summary: A data warehouse is a central information hub that stores and organizes vast amounts of data from different sources within an organization. Unlike operational databases focused on daily tasks, data warehouses are designed for analysis, enabling historical trend exploration and informed decision-making.

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Dataversity

MARCH 2, 2022

Without effective and comprehensive validation, a data warehouse becomes a data swamp. With the accelerating adoption of Snowflake as the cloud data warehouse of choice, the need for autonomously validating data has become critical.

Data Quality 52

Data Quality Data Warehouse Cloud Data Data Governance 52

Dataversity

JANUARY 28, 2021

It has been ten years since Pentaho Chief Technology Officer James Dixon coined the term “data lake.” While data warehouse (DWH) systems have had longer existence and recognition, the data industry has embraced the more […]. The post A Bridge Between Data Lakes and Data Warehouses appeared first on DATAVERSITY.

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Data Lakes Data Warehouse Data Quality Data Governance 59

Dataversity

MARCH 1, 2021

Data warehouse (DW) testers with data integration QA skills are in demand. Data warehouse disciplines and architectures are well established and often discussed in the press, books, and conferences. Each business often uses one or more data […]. Each business often uses one or more data […].

Data Warehouse 52

Data Warehouse ETL Data Governance Data Quality 52

Pickl AI

NOVEMBER 15, 2023

Discover the nuanced dissimilarities between Data Lakes and Data Warehouses. Data management in the digital age has become a crucial aspect of businesses, and two prominent concepts in this realm are Data Lakes and Data Warehouses. It acts as a repository for storing all the data.

Data Lakes 52

Data Lakes Data Warehouse Database ETL 52

IBM Journey to AI blog

JANUARY 5, 2023

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

Data Quality 52

Data Quality Data Lakes Data Warehouse Big Data 52

Dataversity

FEBRUARY 1, 2021

Project sponsors seek to empower more and better data-driven decisions and actions throughout their enterprise; they intend to expand their […]. The post Avoid These Mistakes on Your Data Warehouse and BI Projects: Part 3 appeared first on DATAVERSITY.

Data Warehouse 59

Data Warehouse Business Intelligence Business Intelligence Data Profiling 59

Pickl AI

OCTOBER 19, 2023

Data quality plays a significant role in helping organizations strategize their policies that can keep them ahead of the crowd. Hence, companies need to adopt the right strategies that can help them filter the relevant data from the unwanted ones and get accurate and precise output.

Data Quality 52

Data Quality Data Governance Data Warehouse Machine Learning 52

Dataversity

JANUARY 11, 2021

Project sponsors seek to empower more and better data-driven decisions and actions throughout their enterprise; they intend to expand their user base for […]. The post Avoid These Mistakes on Your Data Warehouse and BI Projects: Part 2 appeared first on DATAVERSITY.

Data Warehouse 59

Data Warehouse Business Intelligence Business Intelligence Data Profiling 59

Dataversity

AUGUST 9, 2021

As I’ve been working to challenge the status quo on Data Governance – I get a lot of questions about how it will “really” work. The Business Dislikes Our Data Warehouse appeared first on DATAVERSITY. I’ll be sharing these questions and answers via this DATAVERSITY® series. Last year I wrote […]. The post Dear Laura: Help!

Data Warehouse 52

Data Warehouse Data Governance Data Quality 52

Dataversity

AUGUST 9, 2021

As I’ve been working to challenge the status quo on Data Governance – I get a lot of questions about how it will “really” work. The Business Dislikes Our Data Warehouse appeared first on DATAVERSITY. I’ll be sharing these questions and answers via this DATAVERSITY® series. Last year I wrote […]. The post Dear Laura: Help!

Data Warehouse 52

Data Warehouse Data Governance Data Quality 52

DagsHub

AUGUST 23, 2024

As such, the quality of their data can make or break the success of the company. This article will guide you through the concept of a data quality framework, its essential components, and how to implement it effectively within your organization. What is a data quality framework?

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Data Quality Data Governance Machine Learning Machine Learning 52

Dataconomy

OCTOBER 8, 2024

Some of the challenges include discrepancies in the data, inaccurate data, corrupted data and security vulnerabilities. Adding to these headaches, it can be tricky for developers to identify the source of their inaccurate or corrupted data, which complicates efforts to maintain data quality.

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ODSC - Open Data Science

SEPTEMBER 27, 2023

In this article, we will delve into the concept of data lakes, explore their differences from data warehouses and relational databases, and discuss the significance of data version control in the context of large-scale data management. Schema Enforcement: Data warehouses use a “schema-on-write” approach.

Data Lakes 98

Data Lakes Data Warehouse Database Big Data 98

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.

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Dataversity

AUGUST 15, 2022

If data is the new oil, then high-quality data is the new black gold. Just like with oil, if you don’t have good data quality, you will not get very far. So, what can you do to ensure your data is up to par and […]. You might not even make it out of the starting gate.

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Data Observability Data Quality Data Lakes Data Warehouse 52

phData

OCTOBER 25, 2024

“Quality over Quantity” is a phrase we hear regularly in life, but when it comes to the world of data, we often fail to adhere to this rule. Data Quality Monitoring implements quality checks in operational data processes to ensure that the data meets pre-defined standards and business rules.

Data Quality 52

Data Quality Data Pipeline Data Governance Database 52

Dataversity

DECEMBER 11, 2023

Organizations learned a valuable lesson in 2023: It isn’t sufficient to rely on securing data once it has landed in a cloud data warehouse or analytical store. As a result, data owners are highly motivated to explore technologies in 2024 that can protect data from the moment it begins its journey in the source systems.

Data Governance 111

Data Governance Data Warehouse Cloud Data Analytics 111

The Data Administration Newsletter

FEBRUARY 1, 2022

In this blog, we will discuss a common problem for data warehouses that are designed to maintain data quality and provide evidence of accuracy. Without verification, the data can’t be trusted. Enter the mundane, but necessary, task of data reconciliation. This is often a time-consuming and wasteful process.

Data Warehouse 59

Data Warehouse Data Quality Data Governance 59

The Data Administration Newsletter

MAY 16, 2023

Data quality management (DQM) has advanced considerably over the years. The full extent of the problem was first recognized during the data warehouse movement in the 1980s.

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Data Quality Data Warehouse Data Governance 52

Tableau

SEPTEMBER 13, 2021

release enhances Tableau Data Management features to provide a trusted environment to prepare, analyze, engage, interact, and collaborate with data. Automate your Prep flows in a defined sequence, with automatic data quality warnings for any failed runs. Enable data quality warnings for email subscriptions to dashboards.

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Tableau Data Quality Data Preparation Data Warehouse 102

Tableau

SEPTEMBER 13, 2021

release enhances Tableau Data Management features to provide a trusted environment to prepare, analyze, engage, interact, and collaborate with data. Automate your Prep flows in a defined sequence, with automatic data quality warnings for any failed runs. Enable data quality warnings for email subscriptions to dashboards.

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Dataversity

MAY 26, 2023

Suppose you’re in charge of maintaining a large set of data pipelines from cloud storage or streaming data into a data warehouse. How can you ensure that your data meets expectations after every transformation? That’s where data quality testing comes in.

Data Pipeline 52

Data Pipeline Data Warehouse Data Quality Data Observability 52

Pickl AI

OCTOBER 6, 2024

It is a crucial data integration process that involves moving data from multiple sources into a destination system, typically a data warehouse. This process enables organisations to consolidate their data for analysis and reporting, facilitating better decision-making. ETL stands for Extract, Transform, and Load.

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ETL Data Warehouse Data Quality Data Lakes 52

AWS Machine Learning Blog

OCTOBER 9, 2024

The service, which was launched in March 2021, predates several popular AWS offerings that have anomaly detection, such as Amazon OpenSearch , Amazon CloudWatch , AWS Glue Data Quality , Amazon Redshift ML , and Amazon QuickSight. You can review the recommendations and augment rules from over 25 included data quality rules.

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AWS Machine Learning Blog

APRIL 3, 2025

When needed, the system can access an ODAP data warehouse to retrieve additional information. The company aims to integrate additional data sources, including other mission-critical systems, into ODAP. OMRON is also exploring more advanced generative AI use cases, such as INSERT_INITIATIVES.

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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.

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Dataversity

DECEMBER 16, 2020

According to IDC, the size of the global datasphere is projected to reach 163 ZB by 2025, leading to the disparate data sources in legacy systems, new system deployments, and the creation of data lakes and data warehouses. Most organizations do not utilize the entirety of the data […].

Data Warehouse 69

Data Warehouse Data Lakes Data Profiling Data Quality 69

Tableau

APRIL 18, 2022

We’ve infused our values into our platform, which supports data fabric designs with a data management layer right inside our platform, helping you break down silos and streamline support for the entire data and analytics life cycle. . Analytics data catalog. Data quality and lineage. Metadata management.

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Tableau Data Quality Analytics Analytics 102

Tableau

APRIL 18, 2022

We’ve infused our values into our platform, which supports data fabric designs with a data management layer right inside our platform, helping you break down silos and streamline support for the entire data and analytics life cycle. . Analytics data catalog. Data quality and lineage. Metadata management.

Tableau 98

Tableau Data Quality Analytics Analytics 98