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.

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Towards AI

JANUARY 28, 2024

To start, get to know some key terms from the demo: Snowflake: The centralized source of truth for our initial data Magic ETL: Domo’s tool for combining and preparing data tables ERP: A supplemental data source from Salesforce Geographic: A supplemental data source (i.e., Instagram) used in the demo Why Snowflake?

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ETL Python Database Data Preparation 111

phData

AUGUST 9, 2023

With ELT, we first extract data from source systems, then load the raw data directly into the data warehouse before finally applying transformations natively within the data warehouse. This is unlike the more traditional ETL method, where data is transformed before loading into the data warehouse.

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ETL Data Warehouse Cloud Data Big Data 52

Dataconomy

SEPTEMBER 4, 2023

Define data ownership, access controls, and data management processes to maintain the integrity and confidentiality of your data. Data integration: Integrate data from various sources into a centralized cloud data warehouse or data lake. Ensure that data is clean, consistent, and up-to-date.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

phData

OCTOBER 9, 2023

As organizations embrace the benefits of data vault, it becomes crucial to ensure optimal performance in the underlying data platform. One such platform that has revolutionized cloud data warehousing is the Snowflake Data Cloud. However, joining tables using a hash key can take longer than a sequential key.

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phData

SEPTEMBER 2, 2024

In this blog, we will cover the best practices for developing jobs in Matillion, an ETL/ELT tool built specifically for cloud database platforms. Some of the supported ones for the Matillion ETL/ELT are GitHub , Bitbucket , and Azure DevOps. To do this, we need to integrate third-party secret managers in Matillion ETL.

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phData

FEBRUARY 21, 2025

With a traditional on-prem data warehouse, an organization will face more substantial Capital Expenditures (CapEx), or one-time costs, such as infrastructure setup, network configuration, and investments in servers and storage devices. When investing in a cloud data warehouse, the Operational Expenditures (OpEx) will be larger.

Data Warehouse 52

Data Warehouse Cloud Data ETL Cloud Computing 52

Smart Data Collective

APRIL 29, 2020

Data management approaches are varied and may be categorised in the following: Cloud data management. The storage and processing of data through a cloud-based system of applications. Master data management. Extraction, Transform, Load (ETL). Private cloud deployments are also possible with Azure.

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phData

MARCH 8, 2023

Fivetran is an automated data integration platform that offers a convenient solution for businesses to consolidate and sync data from disparate data sources. With over 160 data connectors available, Fivetran makes it easy to move data out of, into, and across any cloud data platform in the market.

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Data Warehouse Data Engineering Data Engineer Data Engineering 96

Alation

JANUARY 17, 2023

Data ingestion/integration services. Reverse ETL tools. Data orchestration tools. These tools are used to manage big data, which is defined as data that is too large or complex to be processed by traditional means. How Did the Modern Data Stack Get Started? A Note on the Shift from ETL to ELT.

Data Warehouse 52

Data Warehouse ETL Tableau Cloud Data 52

phData

JULY 17, 2023

Over the past few decades, the corporate data landscape has changed significantly. The shift from on-premise databases and spreadsheets to the modern era of cloud data warehouses and AI/ LLMs has transformed what businesses can do with data. This is where Fivetran and the Modern Data Stack come in.

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phData

JUNE 6, 2024

Data gets ingested, centralized, and deployed within your cloud data warehouse. This allows companies to use their pre-existing data tools and prevents the need for costly setups. Companies need to bring in data from a wide variety of sources to get a holistic view of the customer.

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Data Warehouse Cloud Data ETL Data Modeling 52

Precisely

APRIL 3, 2023

How can an organization enable flexible digital modernization that brings together information from multiple data sources, while still maintaining trust in the integrity of that data? To speed analytics, data scientists implemented pre-processing functions to aggregate, sort, and manage the most important elements of the data.

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ETL Analytics Analytics Database 52

Data Science Dojo

JULY 3, 2024

Big Data Technologies : Handling and processing large datasets using tools like Hadoop, Spark, and cloud platforms such as AWS and Google Cloud. Data Processing and Analysis : Techniques for data cleaning, manipulation, and analysis using libraries such as Pandas and Numpy in Python.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

phData

APRIL 29, 2024

Understanding Fivetran Fivetran is a popular Software-as-a-Service platform that enables users to automate the movement of data and ETL processes across diverse sources to a target destination. For a longer overview, along with insights and best practices, please feel free to jump back to the previous blog.

SQL 52

SQL Data Warehouse Azure Cloud Data 52

Smart Data Collective

OCTOBER 17, 2022

If you haven’t already, moving to the cloud can be a realistic alternative. Cloud data warehouses provide various advantages, including the ability to be more scalable and elastic than conventional warehouses. Can’t get to the data.

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Big Data Big Data Data Engineering Data Engineer 119

Data Science Blog

JUNE 27, 2023

It offers the advantage of having a single ETL platform to develop and maintain. It is well-suited for developing data systems that emphasize online learning and do not require a separate batch layer. The Kappa architecture is particularly suitable when event streaming or real-time processing use cases are predominant.

Big Data 130

Big Data Big Data Apache Kafka Database 130

AWS Machine Learning Blog

AUGUST 4, 2023

As a result, businesses can accelerate time to market while maintaining data integrity and security, and reduce the operational burden of moving data from one location to another. With Einstein Studio, a gateway to AI tools on the data platform, admins and data scientists can effortlessly create models with a few clicks or using code.

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phData

JANUARY 5, 2023

Python has proven proficient in setting up pipelines, maintaining data flows, and transforming data with its simple syntax and proficiency in automation. Having been built completely for and in the cloud, the Snowflake Data Cloud has become an industry leader in cloud data platforms.

Python 52

Python Data Engineering Data Engineer Data Engineering 52

phData

SEPTEMBER 27, 2024

Using cloud data services can be nerve-wracking for some companies. Yes, it’s cheaper, faster, and more efficient than keeping your data on-premises, but you’re at the provider’s mercy regarding your available data.

Cloud Data 52

Cloud Data Database ETL Data Visualization 52

Alation

APRIL 14, 2023

Last week, the Alation team had the privilege of joining IT professionals, business leaders, and data analysts and scientists for the Modern Data Stack Conference in San Francisco. In “The modern data stack is dead, long live the modern data stack!” Cloud costs are growing prohibitive.

Data Pipeline 52

Data Pipeline Data Warehouse Cloud Data ETL 52

Precisely

JUNE 2, 2023

As companies strive to leverage AI/ML, location intelligence, and cloud analytics into their portfolio of tools, siloed mainframe data often stands in the way of forward momentum. Many organizations are using CDC technology to push data to cloud data platforms like Snowflake, Redshift, Databricks, and Kafka.

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Precisely

MAY 23, 2024

The sudden popularity of cloud data platforms like Databricks , Snowflake , Amazon Redshift, Amazon RDS, Confluent Cloud , and Azure Synapse has accelerated the need for powerful data integration tools that can deliver large volumes of information from transactional applications to the cloud reliably, at scale, and in real time.

Data Governance 64

Data Governance ETL Data Pipeline Azure 64

phData

JANUARY 4, 2023

Snowflake works with an entire ecosystem of tools including Extract Transform and Load (ETL), data integration, and analysis tools. Disaster Recovery Snowflake allows for an easy and automatic backup of data and enables faster disaster recovery of critical IT systems.

Data Warehouse 52

Data Warehouse SQL Database ETL 52

phData

NOVEMBER 28, 2023

Matillion is also built for scalability and future data demands, with support for cloud data platforms such as Snowflake Data Cloud , Databricks, Amazon Redshift, Microsoft Azure Synapse, and Google BigQuery, making it future-ready, everyone-ready, and AI-ready. Why Does it Matter?

Data Warehouse 52

Data Warehouse Data Pipeline ETL Azure 52

phData

FEBRUARY 14, 2023

This may result in data inconsistency when UPDATE and DELETE operations are performed on the target database. For simple and quick replication to Snowflake, Matillion offers Data Loader, a SaaS tool that migrates data from various data sources. Replication of calculated values is not supported during Change Processing.

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Data Warehouse Azure AWS Database 59

phData

JUNE 14, 2023

In recent years, data engineering teams working with the Snowflake Data Cloud platform have embraced the continuous integration/continuous delivery (CI/CD) software development process to develop data products and manage ETL/ELT workloads more efficiently.

Data Pipeline 52

Data Pipeline Database SQL Data Engineering 52

Precisely

MAY 23, 2024

The sudden popularity of cloud data platforms like Databricks , Snowflake , Amazon Redshift, Amazon RDS, Confluent Cloud , and Azure Synapse has accelerated the need for powerful data integration tools that can deliver large volumes of information from transactional applications to the cloud reliably, at scale, and in real time.

Data Governance 52

Data Governance ETL Data Pipeline Azure 52

phData

SEPTEMBER 4, 2024

ThoughtSpot was designed to be low-code and easy for anyone to use across a business to generate insights and explore data. ThoughSpot can easily connect to top cloud data platforms such as Snowflake AI Data Cloud , Oracle, SAP HANA, and Google BigQuery.

Analytics 52

Analytics Analytics SQL ETL 52

Alation

OCTOBER 27, 2022

Few actors in the modern data stack have inspired the enthusiasm and fervent support as dbt. This data transformation tool enables data analysts and engineers to transform, test and document data in the cloud data warehouse. But what does this mean from a practitioner perspective?

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Data Analyst Data Scientist Analytics Analytics 52

phData

NOVEMBER 30, 2023

The Snowflake Data Cloud is a leading cloud data platform that provides various features and services for data storage, processing, and analysis. A new feature that Snowflake offers is the ability to create alerts based on data in Snowflake. How does CRON work for scheduling alerts?

SQL 52

SQL Cloud Data Database ETL 52

phData

FEBRUARY 7, 2024

The Snowflake Data Cloud is a leading cloud data platform that provides various features and services for data storage, processing, and analysis. A new feature that Snowflake offers is called Snowpark, which provides an intuitive library for querying and processing data at scale in Snowflake.

Python 52

Python ML ML SQL 52

Alation

APRIL 4, 2023

This expanded connector to Databricks Unity Catalog does just that, delivering to joint customers a comprehensive view of all cloud data. New Connectivity for dbt Modern data engineers confront complex, challenging data environments and need to empower data users for self-service. Now with this new 2023.1

DataOps 52

DataOps Data Engineering Data Engineer Data Engineering 52

Dataversity

SEPTEMBER 6, 2021

The rush to become data-driven is more heated, important, and pronounced than it has ever been. Businesses understand that if they continue to lead by guesswork and gut feeling, they’ll fall behind organizations that have come to recognize and utilize the power and potential of data. Click to learn more about author Mike Potter.

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Data Warehouse Data Lakes ETL Cloud Data 98

Alation

MARCH 22, 2022

As the latest iteration in this pursuit of high-quality data sharing, DataOps combines a range of disciplines. It synthesizes all we’ve learned about agile, data quality , and ETL/ELT. And it injects mature process control techniques from the world of traditional engineering.

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DataOps Data Pipeline Data Engineering Data Engineer 52

phData

JANUARY 19, 2024

Matillion is also built for scalability and future data demands, with support for cloud data platforms such as Snowflake Data Cloud , Databricks, Amazon Redshift, Microsoft Azure Synapse, and Google BigQuery, making it future-ready, everyone-ready, and AI-ready.

Data Pipeline 52

Data Pipeline Data Warehouse ETL Azure 52

Mlearning.ai

JULY 10, 2023

In my 7 years of Data Science journey, I’ve been exposed to a number of different databases including but not limited to Oracle Database, MS SQL, MySQL, EDW, and Apache Hadoop. You can use stored procedures to handle complex ETL processes, make API calls, and perform data validation.

SQL 52

SQL Database Apache Hadoop Data Science 52