Monte Carlo

JANUARY 10, 2024

In this article, we present six intrinsic data quality techniques that serve as both compass and map in the quest to refine the inner beauty of your data. Data Profiling 2. Data Cleansing 3. Data Validation 4. Data Auditing 5. Data Governance 6. This is known as data governance.

Data Cleanse 52

Data Cleanse Data Engineering Data Engineer Engineering 52

Data Engineering Weekly

JUNE 18, 2023

Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make it easy to collect data from every application, website, and SaaS platform, then activate it in your warehouse and business tools. Data management is critical for any organization to succeed in this AI world.

Data Engineering 52

Data Engineering Data Engineer Engineering MySQL 52

Databand.ai

AUGUST 30, 2023

The DataOps framework is a set of practices, processes, and technologies that enables organizations to improve the speed, accuracy, and reliability of their data management and analytics operations. This can be achieved through the use of automated data ingestion, transformation, and analysis tools.

Data Governance 52

Data Governance Data Pipeline Government Data Cleanse 52

Edureka

FEBRUARY 7, 2023

An Azure Data Engineer is responsible for designing, implementing, and maintaining data management and data processing systems on the Microsoft Azure cloud platform. They work with large and complex data sets and are responsible for ensuring that data is stored, processed, and secured efficiently and effectively.

Data Engineering 52

Data Engineering Data Engineer Engineering Programming Language 52

Towards Data Science

JUNE 8, 2023

Some organizations will attempt to diffuse the responsibility widely across data stewards, data owners, data engineering and governance committees, each owning a fraction of the data value chain. Why is data quality ownership important? The whole needs to be greater than the sum of its parts.

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Data Governance Government Generalist Data Engineering 80

Monte Carlo

JUNE 6, 2023

Some organizations will attempt to diffuse the responsibility widely across data stewards, data owners, data engineering and governance committees, each owning a fraction of the data value chain. Table of Contents Why is important to answer who is responsible for data quality?

Data Governance 98

Data Governance Government Data Data Engineering 98

Silectis

FEBRUARY 17, 2021

In this blog post, we’ll walk you through how data science and data engineering are complementary disciplines. We’ll also delineate a third category: data analysis. We’ll explore how both data engineering and data science should be marshaled to make better decisions. What is Data Science, Really?

Data Science 52

Data Science Data Engineering Data Engineer Engineering 52

ProjectPro

FEBRUARY 21, 2023

With so many data engineering certifications available , choosing the right one can be a daunting task. There are over 133K data engineer job openings in the US, but how will you stand out in such a crowded job market? The answer is- by earning professional data engineering certifications! AWS or Azure?

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Certification Data Engineering Data Engineer Engineering 52

Databand.ai

AUGUST 30, 2023

Data Testing Tools: Key Capabilities and 6 Tools You Should Know Helen Soloveichik August 30, 2023 What Are Data Testing Tools? Data testing tools are software applications designed to assist data engineers and other professionals in validating, analyzing, and maintaining data quality.

Data Cleanse 52

Data Cleanse Data Validation Data Pipeline Datasets 52

Databand.ai

JULY 19, 2023

However, their importance has grown significantly in recent years due to the increasing complexity of data architectures and the growing need for data governance and compliance. In this article: Why Are Data Lineage Tools Important? It provides context for data, making it easier to understand and manage.

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Pipeline-centric Data Governance Metadata Government 52

Data Engineering Podcast

JUNE 5, 2022

In this episode Sean Falconer explains the idea of a data privacy vault and how this new architectural element can drastically reduce the potential for making a mistake with how you manage regulated or personally identifiable information. By the time errors have made their way into production, it’s often too late and damage is done.

Data Security 100

Data Security Metadata MongoDB Scala 100

Data Engineering Podcast

JULY 10, 2022

They also discuss how they have established a guild system for training and supporting data professionals in the organization. Modern data teams are dealing with a lot of complexity in their data pipelines and analytical code. Tired of deploying bad data? Need to automate data pipelines with less red tape?

Metadata 100

Metadata MongoDB MySQL Data Pipeline 100

Databand.ai

AUGUST 30, 2023

DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. It aims to streamline data ingestion, processing, and analytics by automating and integrating various data workflows.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Data Engineering Podcast

JULY 12, 2021

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management You listen to this show to learn about all of the latest tools, patterns, and practices that power data engineering projects across every domain. Closing Announcements Thank you for listening!

Designing 100

Designing Data Warehouse Data Governance Consulting 100

Data Engineering Podcast

APRIL 26, 2021

In this episode Maxime Beauchemin discusses how data engineers can use Superset to provide self service access to data and deliver analytics. He digs into how it integrates with your data stack, how you can extend it to fit your use case, and why open source systems are a good choice for your business intelligence.

Business Intelligence 100

Business Intelligence Data Warehouse Hadoop Data Pipeline 100

Data Engineering Podcast

NOVEMBER 23, 2020

Summary One of the oldest aphorisms about data is "garbage in, garbage out", which is why the current boom in data quality solutions is no surprise. He also shares how his own product is designed and the challenges that are involved in building a system to help data engineers manage the complexity of a data platform.

Hadoop 100

Hadoop Data Pipeline BI Data 100

Data Engineering Podcast

FEBRUARY 24, 2020

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode.

IT 100

IT Data Lake Data Pipeline Media 100

Data Engineering Podcast

APRIL 5, 2021

She explains how the design of the platform is informed by the needs of managing data projects for large and small teams across her previous roles, how it integrates with your existing systems, and how it can work to bring everyone onto the same page. RudderStack’s smart customer data pipeline is warehouse-first.

Data Warehouse 100

Data Warehouse Data Pipeline BI Metadata 100

Data Engineering Podcast

DECEMBER 14, 2020

Summary As a data engineer you’re familiar with the process of collecting data from databases, customer data platforms, APIs, etc. At YipitData they rely on a variety of alternative data sources to inform investment decisions by hedge funds and businesses.

Data Analytics 100

Data Analytics Building MySQL Data 100

AltexSoft

FEBRUARY 11, 2023

Data architecture is the organization and design of how data is collected, transformed, integrated, stored, and used by a company. Bad data management be like, Source: Makeameme Data architects are sometimes confused with other roles inside the data science team. Feel free to enjoy it. Feel free to enjoy it.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Ascend.io

JANUARY 10, 2024

Visual representation of Conway’s Law ( source ) Read More: The Chief AI Officer: Avoid The Trap of Conway’s Law Process: Ensuring Data Readiness The backbone of successful AI implementation is robust data management processes. AI models are only as good as the data they consume, making continuous data readiness crucial.

Data Pipeline 52

Data Pipeline Government Data Governance Raw Data 52

The Modern Data Company

JULY 31, 2023

Achieving such flexible loops requires interoperable code, declarative change management, and independent infra provisioning (via IaC), akin to Software 101. Unified governance, particularly challenging in fragmented data stacks with numerous tools and data assets, is addressed through the infrastructure piece of Data Products.

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Government Data Governance Architecture Data Pipeline 98

Data Engineering Podcast

OCTOBER 15, 2021

They also share their ambitions for the near future of adding data observability and data quality management features. Supercharge your business teams with customer data using Hightouch for Reverse ETL today. Modern Data teams are dealing with a lot of complexity in their data pipelines and analytical code.

Metadata 100

Metadata BI Data Warehouse Government 100

Data Engineering Podcast

OCTOBER 19, 2020

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management What are the pieces of advice that you wish you had received early in your career of data engineering? If you hand a book to a new data engineer, what wisdom would you add to it?

Machine Learning 100

Machine Learning Data Engineering Data Engineer Data 100

Databand.ai

AUGUST 30, 2023

Data testing tools: Key capabilities you should know Helen Soloveichik August 30, 2023 Data testing tools are software applications designed to assist data engineers and other professionals in validating, analyzing and maintaining data quality. This is part of a series of articles about data quality.

Data Cleanse 52

Data Cleanse Data Pipeline Datasets Data Validation 52

Data Engineering Podcast

NOVEMBER 9, 2020

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management What are the pieces of advice that you wish you had received early in your career of data engineering? If you hand a book to a new data engineer, what wisdom would you add to it?

Building 100

Building PostgreSQL BI Metadata 100

Ascend.io

DECEMBER 19, 2023

That’s what we call a data pipeline. It could just as well be ‘ELT for Snowflake’ The key takeaway is that these terms are representative of the actual activity being undertaken: the construction and management of data pipelines within the Snowflake environment.

ETL Tools 52

ETL Tools IT Data Pipeline Data Warehouse 52

Data Engineering Podcast

NOVEMBER 30, 2020

With the increasing pace of change and the need for up to date analytics the need to integrate that data in near real time is growing. With the improvements and increased variety of options for streaming data engines and improved tools for change data capture it is possible for data teams to make that goal a reality.

Data Integration 100

Data Integration Coding BI Kafka 100

Ascend.io

SEPTEMBER 5, 2023

In the fast-evolving landscape of cloud data solutions, Snowflake has consistently been at the forefront of innovation, offering enterprises sophisticated tools to optimize their data management. This enhances data governance and aids in decision-making. This paves the way for new interactions and capabilities.

IT 59

IT Scala Java Programming Language 59

Databand.ai

JULY 5, 2023

What Are Data Observability Tools? Data observability tools are software solutions that oversee, analyze, and improve the performance of data pipelines. Data observability tools allow teams to detect issues such as missing values, duplicate records, or inconsistent formats early on before they affect downstream processes.

Data Pipeline 52

Data Pipeline Data Lake Data Warehouse Datasets 52

Knowledge Hut

DECEMBER 26, 2023

Data Engineering Data Engineering involves various operations like creating data pipelines, strategizing data management plans, processing data, and many more. Data Management Data management is an integral part of high-scale organizations.

Data Science 52

Data Science Scala Programming Language R (Programming) 52

Monte Carlo

JUNE 16, 2023

Data integrity and quality may seem similar at first glance, and they are sometimes used interchangeably in everyday life, but they play unique roles in successful data management. Impact Now that you understand the purpose of data integrity and data quality, what is their impact on data management and decision-making?

Data Integration 52

Data Integration Hospitality Banking Healthcare 52

DataKitchen

JANUARY 5, 2021

Execution of this mission requires the contribution of several groups: data center/IT, data engineering, data science, data visualization, and data governance. Each of the roles mentioned above views the world through a preferred set of tools: Data Center/IT – Servers, storage, software.

Data Governance 59

Data Governance Government Metadata Data Science 59

The Modern Data Company

JULY 31, 2023

Achieving such flexible loops requires interoperable code, declarative change management, and independent infra provisioning (via IaC), akin to Software 101. By omitting the complexity and debt of data pipelines resulting from multiple fragmented tools in the ‘MAD Ecosystem,’ these loops can be efficiently maintained.

Government 52

Government Data Governance Architecture Data Pipeline 52

The Modern Data Company

JULY 31, 2023

Achieving such flexible loops requires interoperable code, declarative change management, and independent infra provisioning (via IaC), akin to Software 101. By omitting the complexity and debt of data pipelines resulting from multiple fragmented tools in the ‘MAD Ecosystem,’ these loops can be efficiently maintained.

Government 52

Government Data Governance Architecture Data Pipeline 52

Databand.ai

JULY 19, 2023

Learn more in our detailed guide to the data ingestion process (coming soon) Best Practices for Effective Data Ingestion Defining Clear Data Governance Policies Data governance involves the overall management of data availability, usability, integrity, and security.

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Data Ingestion Process Data Cleanse Data Governance 52

Monte Carlo

AUGUST 31, 2023

As the data analyst or engineer responsible for managing this data and making it usable, accessible, and trustworthy, rarely a day goes by without having to field some request from your stakeholders. But what happens when the data is wrong? In our opinion, data quality frequently gets a bad rep.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52