Dataversity

JANUARY 27, 2023

Up until recently, feedback forms and […] The post How Reverse ETL Powers Modern Customer Marketing: Concrete Examples appeared first on DATAVERSITY. If you’re part of a customer marketing team, you know that most people would say “not very often.” This is precisely the plight of the average customer marketer.

Data Warehouse 130

Data Warehouse Data Architecture 130

Tim Mitchell

DECEMBER 12, 2020

In this first post in my series on ETL Antipatterns, I’m going to discuss one of the most common missteps when building an extract-transform-load (ETL) process: jumping straight into writing code as a first step. ETL Antipattern: start with writing code Most data architects and developers are intensely curious folks.

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Tim Mitchell

DECEMBER 20, 2020

On the other hand, good documentation – particularly around data movement and ETL processes. The post ETL Antipattern: Skipping The Documentation appeared first on Tim Mitchell.

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Documentation 130

Dataversity

MARCH 29, 2021

Have you ever been in a situation when you had to represent the ETL team by being up late for L3 support only to find out that one of your […]. The post Rethinking Extract Transform Load (ETL) Designs appeared first on DATAVERSITY.

Data Modelling 130

Data Modelling Data Architecture 130

Tim Mitchell

DECEMBER 22, 2020

In this final post in my ETL Antipatterns series, I’ll talk about a common big-picture mistake when building ETL processes: ignoring the fundamental question, “why are we doing this?” ” ETL Antipattern: ignoring the “why?” The post ETL Antipattern: Ignoring the “Why?”

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Tim Mitchell

DECEMBER 18, 2020

” – An unemployed developer Building ETL processes is quite easy. Building ETL processes that deliver accurate results as quickly as possible is substantially more difficult. Modern ETL tools (including my personal favorite, SQL Server Integration Services) make it deceptively easy to create simple load process.

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Simplilearn

JUNE 24, 2022

For this reason, ETL and ETL te. While data can be enhanced by processing, analyzing, and transforming, it can be lost, susceptible to errors, inaccurate, or deficient. Flaws in data may impact business decisions. Read More.

Digital 130

Digital 130

Dataversity

AUGUST 30, 2021

DataOps, which focuses on automated tools throughout the ETL development cycle, responds to a huge challenge for data integration and ETL projects in general. ETL projects are increasingly based on agile processes and automated testing. extract, transform, load) projects are often devoid of automated testing. The […].

Agile 130

Agile Data Warehouse Data Quality Data Architecture 130

Astera

FEBRUARY 26, 2024

However, businesses need to employ the right Azure ETL (Extract, Transform, Load) tools to fully leverage its powerful capabilities. In this article, we will explore the top 5 ETL tools for Azure Data Warehouse that can help streamline data integration and improve overall analytics performance.

Data Warehouse 52

Data Warehouse Data Quality Real-time Data Documentation 52

Astera

FEBRUARY 16, 2024

ETL Using Python: Exploring the Pros vs. Cons Are you looking to automate and streamline your data integration process? ETL (extract, transform, and load) collects data from various sources, applies business rules and transformations, and loads the data into a destination system. Is It Possible to Build ETL Using Python ?

Data Warehouse 52

Data Warehouse Monitoring Data Quality Government 52

Tim Mitchell

DECEMBER 19, 2020

One of the most significant design considerations in ETL process development is the volume of data to be processed. Most ETL processes have time constraints that require them to complete their load operations within a given window, and the time required to process data will often dictate the design of the load.

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Dataversity

JUNE 14, 2021

The post Why ETL Needs Open Source to Address the Long Tail of Integrations appeared first on DATAVERSITY. Over the last year, our team has interviewed more than 200 companies about their data integration use cases. What we discovered is that data integration in 2021 is still a mess. The Unscalable Current Situation At least 80 of […].

Data Architecture 242

Data Architecture 242

Tim Mitchell

DECEMBER 13, 2020

In my continuing series on ETL Antipatterns, I’ll discuss the problem of loading too much data in extract-transform-load processes. ETL Antipattern: processing too much data A common design flaw in enterprise ETL processes is that they are processing too much data.

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Astera

JANUARY 25, 2024

What is Reverse ETL? Reverse ETL (Extract, Transform, Load) is the process of moving data from central data warehouse to operational and analytic tools. So, in simple terms, reverse ETL helps businesses get the right data to the right tools at the right time, making their work easier and more productive.

E-Commerce 52

E-Commerce Data Warehouse Retail Customer Experience 52

Simplilearn

DECEMBER 22, 2022

ETL is an acronym for Extract, Transform and Load, and it's a technique used to extract data from one database, transform it into another format, and then load it into another database. This software has been around since the 1960s, but it's only recently gained popularity as a way to automate moving data around in a database environment.

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ElegantJ BI

JULY 20, 2020

With the right Augmented Analytics Tools , the enterprise can provide predictive analytics for Predictive Modeling , self-serve ETL software for data extraction, transformation and loading (ETL) and a tool for data visualization all in one platform, designed for use by business users with average technical and analytical skills.

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ElegantJ BI

JULY 20, 2020

With the right Augmented Analytics Tools , the enterprise can provide predictive analytics for Predictive Modeling , self-serve ETL software for data extraction, transformation and loading (ETL) and a tool for data visualization all in one platform, designed for use by business users with average technical and analytical skills.

Predictive Analytics 130

Predictive Analytics Data Visualization Visualization 130

ElegantJ BI

JULY 20, 2020

With the right Augmented Analytics Tools , the enterprise can provide predictive analytics for Predictive Modeling , self-serve ETL software for data extraction, transformation and loading (ETL) and a tool for data visualization all in one platform, designed for use by business users with average technical and analytical skills.

Predictive Analytics 130

Predictive Analytics Data Visualization Visualization 130

Astera

FEBRUARY 7, 2024

Zero ETL is a data integration technique where data is transferred from source to destination without the need for a traditional ETL (Extract, Transform, Load) process. Zero – ETL simplifies data accessibility by enabling seamless querying across disparate data sources without necessitating extensive data movement.

Real-time Data 52

Real-time Data Cybersecurity Data Quality Monitoring 52

Dataversity

MAY 17, 2021

There are advantages and disadvantages to both ETL and ELT. The post Understanding the ETL vs. ELT Alphabet Soup and When to Use Each appeared first on DATAVERSITY. To understand which method is a better fit, it’s important to understand what it means when one letter comes before the other.

Data Warehouse 130

Data Warehouse Data Architecture 130

ElegantJ BI

APRIL 10, 2020

Self-Service Data ETL should simplify the tasks of preparing data so users WANT to adopt the tools and use them for data prep and Data Analytics. Self-Service Data ETL should simplify the tasks of preparing data so users WANT to adopt the tools and use them for data prep and Data Analytics. Contact Us today.

Data Analytics 130

Data Analytics Data Analytics Visualization Agile 130

ElegantJ BI

APRIL 10, 2020

Self-Service Data ETL should simplify the tasks of preparing data so users WANT to adopt the tools and use them for data prep and Data Analytics. Self-Service Data ETL should simplify the tasks of preparing data so users WANT to adopt the tools and use them for data prep and Data Analytics. Contact Us today.

Data Analytics 130

Data Analytics Data Analytics Visualization Agile 130

ElegantJ BI

APRIL 10, 2020

Self-Service Data ETL should simplify the tasks of preparing data so users WANT to adopt the tools and use them for data prep and Data Analytics. Self-Service Data ETL should simplify the tasks of preparing data so users WANT to adopt the tools and use them for data prep and Data Analytics. Contact Us today.

Data Analytics 130

Data Analytics Data Analytics Visualization Agile 130

Tim Mitchell

JULY 13, 2020

The SSIS Catalog: Install, Manage, Secure, and Monitor your Enterprise ETL Infrastructure is now available on Amazon in both paperback and Kindle formats. In this book, I introduce the reader to the SSIS catalog and describe how it fits into an enterprise ETL architecture. This book is, by design, narrowly.

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Monitoring 130

ElegantJ BI

SEPTEMBER 4, 2019

Self-service data preparation (when done right) can enable business users to leverage sophisticated, easy-to-use tools for self-serve ETL.

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ElegantJ BI

SEPTEMBER 4, 2019

Self-service data preparation (when done right) can enable business users to leverage sophisticated, easy-to-use tools for self-serve ETL.

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ElegantJ BI

SEPTEMBER 4, 2019

Self-service data preparation (when done right) can enable business users to leverage sophisticated, easy-to-use tools for self-serve ETL.

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Astera

AUGUST 3, 2023

In this context, ETL (Extract, Transform, and Load) emerges as a transformative force that enhances data quality within B2B EDI. By extracting data from various sources, transforming it into a consistent format, and loading it into target systems, ETL ensures standardized, consistent information for strategic decision-making.

Data Quality 52

Data Quality Supply Chain Monitoring Real-time Data 52

Astera

AUGUST 3, 2023

In this context, ETL (Extract, Transform, and Load) emerges as a transformative force that enhances data quality within B2B EDI. By extracting data from various sources, transforming it into a consistent format, and loading it into target systems, ETL ensures standardized, consistent information for strategic decision-making.

Data Quality 52

Data Quality Supply Chain Monitoring Real-time Data 52

Astera

JUNE 6, 2023

ETL architectures have become a crucial solution for managing and processing large volumes of data efficiently, addressing the challenges faced by organizations in the era of big data. This article delves into the complexities of building and optimizing scalable ETL architectures to meet the demands of modern data processing.

Data Quality 52

Data Quality Monitoring Data Warehouse Data Security 52

Domo

NOVEMBER 8, 2021

Enter Domo’s Magic ETL , which makes it simple to combine, transform, and edit data, whether you’re a technical whiz or not. While Domo supports MySQL and Redshift tooling to transform your data, Magic ETL’s drag-and-drop tools make it simple to visually define and sequence operations that transform your data. The power of new Magic.

Visualization 52

Visualization User Experience 52

Sisense

JULY 8, 2020

This is mostly due to the rise of data warehouses, decrease in cost for data storage, and modern ETL tools that make storing and accessing data more approachable than ever before. The ETL process: Foundation of data-driven businesses. Whatever you want to do with data, you have to ETL it first.

Data Warehouse 90

Data Warehouse Embedded Analytics Real-time Data Documentation 90

Astera

MAY 25, 2023

Exploring the World of SSIS ETL ETL, or Extract-Transform-Load, is a critical data integration process that enables businesses to efficiently move and transform large volumes of data from disparate sources. One of the most widely used ETL tools is SSIS ETL, which is Microsoft’s solution for handling these requirements.

Cloud Computing 52

Cloud Computing Visualization Real-time Data Data Quality 52

ElegantJ BI

JANUARY 22, 2019

Augmented Analytics represents the evolution of self-serve data preparation, including ETL for business users, smart visualization, assisted predictive modeling, and Clickless Analytics powered by Natural Language Processing.

Data Discovery 130

Data Discovery Predictive Analytics Innovation Business Intelligence 130

ElegantJ BI

JANUARY 22, 2019

Augmented Analytics represents the evolution of self-serve data preparation, including ETL for business users, smart visualization, assisted predictive modeling, and Clickless Analytics powered by Natural Language Processing.

Data Discovery 130

Data Discovery Predictive Analytics Innovation Business Intelligence 130

ElegantJ BI

JANUARY 22, 2019

Augmented Analytics represents the evolution of self-serve data preparation, including ETL for business users, smart visualization, assisted predictive modeling, and Clickless Analytics powered by Natural Language Processing.

Data Discovery 130

Data Discovery Predictive Analytics Business Intelligence Business Intelligence 130

Domo

APRIL 5, 2024

Data + Magic ETL = Where data transformation becomes a breeze Magic ETL has always been your go-to solution for turning chaotic data into clear insights. Reminder: Magic ETL is Domo’s drag-and-drop and SQL-powered ETL solution.) At Domopalooza 2024, we shared several improvements to Magic ETL. Well, think again.

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