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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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?

Data Quality 52

Data Quality Data Governance Machine Learning Machine Learning 52

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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Data Warehouse Cloud Data Data Governance Database 69

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.

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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.

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Data Science Dojo

JULY 6, 2023

Data engineering tools offer a range of features and functionalities, including data integration, data transformation, data quality management, workflow orchestration, and data visualization. Essential data engineering tools for 2023 Top 10 data engineering tools to watch out for in 2023 1.

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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.

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Data Quality Data Warehouse Cloud Data Data Governance 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.

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Data Quality Data Lakes Data Warehouse Business Intelligence 52

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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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. Welcome to the Dear Laura blog series! I’ll be sharing these questions and answers via this DATAVERSITY® series.

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. Welcome to the Dear Laura blog series! I’ll be sharing these questions and answers via this DATAVERSITY® series.

Data Warehouse 52

Data Warehouse Data Governance Data Quality 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.

Data Lakes 59

Data Lakes Data Warehouse Data Quality Data Governance 59

Alation

JANUARY 26, 2023

These data requirements could be satisfied with a strong data governance strategy. Governance can — and should — be the responsibility of every data user, though how that’s achieved will depend on the role within the organization. How can data engineers address these challenges directly?

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Data Governance Data Engineering Data Engineering Data Engineer 52

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 […].

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Data Warehouse ETL Data Governance Data Quality 52

Pickl AI

NOVEMBER 4, 2024

Key Takeaways Data Engineering is vital for transforming raw data into actionable insights. Key components include data modelling, warehousing, pipelines, and integration. Effective data governance enhances quality and security throughout the data lifecycle. What is Data Engineering?

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Pickl AI

OCTOBER 17, 2024

Introduction ETL plays a crucial role in Data Management. This process enables organisations to gather data from various sources, transform it into a usable format, and load it into data warehouses or databases for analysis. Loading The transformed data is loaded into the target destination, such as a data warehouse.

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ETL Data Warehouse Data Quality Data Governance 52

Alation

SEPTEMBER 7, 2021

In the previous blog , we discussed how Alation provides a platform for data scientists and analysts to complete projects and analysis at speed. In this blog we will discuss how Alation helps minimize risk with active data governance. So why are organizations not able to scale governance? Meet Governance Requirements.

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Data Governance Data Scientist Data Quality Data Profiling 59

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.

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Data Warehouse Business Intelligence Business Intelligence Data Profiling 59

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.

Data Observability 52

Data Observability Data Quality Data Lakes Data Warehouse 52

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.

Data Quality 52

Data Quality Data Warehouse Data Governance 52

Dataversity

NOVEMBER 1, 2021

Whether through acquisition or organic growth, the amount of enterprise data coming into the organization can feel exponential as the business hires more people, opens new locations, and serves new customers. The post Building a Grassroots Data Management and Data Governance Program appeared first on DATAVERSITY.

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Data Governance Data Silos Data Warehouse Data Quality 52

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.

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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.

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Data Pipeline Data Warehouse Data Quality Data Observability 52

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

Pickl AI

AUGUST 11, 2024

Additionally, it addresses common challenges and offers practical solutions to ensure that fact tables are structured for optimal data quality and analytical performance. Introduction In today’s data-driven landscape, organisations are increasingly reliant on Data Analytics to inform decision-making and drive business strategies.

Data Quality 52

Data Quality Data Warehouse Data Governance Business Intelligence 52

Dataconomy

FEBRUARY 23, 2023

Collecting, storing, and processing large datasets Data engineers are also responsible for collecting, storing, and processing large volumes of data. This involves working with various data storage technologies, such as databases and data warehouses, and ensuring that the data is easily accessible and can be analyzed efficiently.

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Big Data Big Data Data Engineering Data Engineering 91

Alation

AUGUST 30, 2022

we are introducing Alation Anywhere, extending data intelligence directly to the tools in your modern data stack, starting with Tableau. We continue to make deep investments in governance, including new capabilities in the Stewardship Workbench, a core part of the Data Governance App. Data governance at scale.

Data Governance 52

Data Governance Data Quality Tableau Data Analyst 52

Pickl AI

OCTOBER 17, 2024

It is a data integration process that involves extracting data from various sources, transforming it into a suitable format, and loading it into a target system, typically a data warehouse. ETL is the backbone of effective data management, ensuring organisations can leverage their data for informed decision-making.

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ETL Data Warehouse SQL Data Quality 52

phData

SEPTEMBER 19, 2023

Cost reduction by minimizing data redundancy, improving data storage efficiency, and reducing the risk of errors and data-related issues. Data Governance and Security By defining data models, organizations can establish policies, access controls, and security measures to protect sensitive data.

Data Lakes 52

Data Lakes Data Models Data Modeling Data Warehouse 52

IBM Journey to AI blog

JULY 3, 2024

Multiple data applications and formats make it harder for organizations to access, govern, manage and use all their data for AI effectively. Scaling data and AI with technology, people and processes Enabling data as a differentiator for AI requires a balance of technology, people and processes.

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Precisely

JULY 18, 2024

While data fabric is not a standalone solution, critical capabilities that you can address today to prepare for a data fabric include automated data integration, metadata management, centralized data governance, and self-service access by consumers. Increase metadata maturity.

Data Lakes 52

Data Lakes Data Warehouse Data Governance Machine Learning 52

IBM Journey to AI blog

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.

Data Quality 52

Data Quality Data Governance Data Wrangling Data Scientist 52

Dataversity

FEBRUARY 13, 2024

Are you drowning in data? Feeling shackled by rigid data warehouses that can’t keep pace with your ever-evolving business needs? Traditional data storage strategies are crumbling under the weight of diverse data sources, leaving you with limited analytics and frustrated decisions. You’re not alone.

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Alation

OCTOBER 21, 2021

But, on the back end, data lakes give businesses a common repository to collect and store data, streamlined usage from a single source, and access to the raw data necessary for today’s advanced analytics and artificial intelligence (AI) needs. Irrelevant data. Ungoverned data. Subscribe to Alation's Blog.

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Data Lakes Data Governance Data Warehouse Business Intelligence 52

Dataversity

FEBRUARY 10, 2023

It’s no surprise that, in 2023, business enterprises want to become truly data-driven organizations. For many of these organizations, the path toward becoming more data-driven lies in the power of data lakehouses, which combine elements of data warehouse architecture with data lakes.

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Data Lakes Data Warehouse Data Quality Data Governance 52

Alation

MAY 16, 2023

Machine Learning Data pipelines feed all the necessary data into machine learning algorithms, thereby making this branch of Artificial Intelligence (AI) possible. Data Quality When using a data pipeline, data consistency, quality, and reliability are often greatly improved.

Data Pipeline 69

Data Pipeline Data Governance Data Lakes Data Warehouse 69

Alation

DECEMBER 15, 2022

March 2015: Alation emerges from stealth mode to launch the first official data catalog to empower people in enterprises to easily find, understand, govern and use data for informed decision making that supports the business. May 2016: Alation named a Gartner Cool Vendor in their Data Integration and Data Quality, 2016 report.

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