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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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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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

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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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

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). Data transformation.

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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? No problem.

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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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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.

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phData

FEBRUARY 14, 2023

Data integration is essentially the Extract and Load portion of the Extract, Load, and Transform (ELT) process. Data ingestion involves connecting your data sources, including databases, flat files, streaming data, etc, to your data warehouse. Snowflake provides native ways for data ingestion.

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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.

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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.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

phData

JANUARY 4, 2023

Why You Should Consider Migrating from Netezza to Snowflake With Netezza, IBM was one of the first companies to provide a data warehousing solution to allow organizations to analyze and manage large amounts of data. However, as technology has evolved, the need for more advanced, agile data warehousing solutions has become apparent.

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phData

JULY 10, 2024

Unlike traditional BI tools, its user-friendly interface ensures that users of all technical levels can seamlessly interact with data. The platform’s integration with cloud data warehouses like Snowflake AI Data Cloud , Google BigQuery, and Amazon Redshift makes it a vital tool for organizations harnessing big data.

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IBM Journey to AI blog

JULY 17, 2023

It is supported by querying, governance, and open data formats to access and share data across the hybrid cloud. Through workload optimization across multiple query engines and storage tiers, organizations can reduce data warehouse costs by up to 50 percent.

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AI AI Machine Learning Machine Learning 75

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.

Big Data 108

Big Data Big Data Data Engineer Data Engineering 108

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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phData

FEBRUARY 5, 2024

There are many different third-party tools that work with Snowflake: Fivetran Fivetran is a tool dedicated to replicating applications, databases, events, and files into a high-performance data warehouse, such as Snowflake.

SQL 52

SQL Database Data Quality Data Warehouse 52

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.

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Data Pipeline Database SQL 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. Additional setup is typically optional.

Data Pipeline 52

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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

phData

SEPTEMBER 27, 2024

If the event log is your customer’s diary, think of persistent staging as their scrapbook – a place where raw customer data is collected, organized, and kept for future reference. In traditional ETL (Extract, Transform, Load) processes in CDPs, staging areas were often temporary holding pens for data.

Data Modeling 52

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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

JANUARY 25, 2022

On the policy front, a feature like Policy Center empowers users to enforce and track policies at scale; this ensures that people use data compliantly, and organizations are prepared for compliance audits. See Gartner’s “ How DataOps Amplifies Data and Analytics Business Value ”).

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phData

OCTOBER 28, 2024

Modern low-code/no-code ETL tools allow data engineers and analysts to build pipelines seamlessly using a drag-and-drop and configure approach with minimal coding. One such option is the availability of Python Components in Matillion ETL, which allows us to run Python code inside the Matillion instance.

Python 52

Python ETL AWS Database 52

Dataversity

APRIL 1, 2021

In the data-driven world we live in today, the field of analytics has become increasingly important to remain competitive in business. In fact, a study by McKinsey Global Institute shows that data-driven organizations are 23 times more likely to outperform competitors in customer acquisition and nine times […].

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Dataversity

MARCH 17, 2021

I do not think it is an exaggeration to say data analytics has come into its own over the past decade or so. What started out as an attempt to extract business insights from transactional data in the ’90s and early 2000s has now transformed into an […]. The post Is Lakehouse Architecture a Grand Unification in Data Analytics?

Analytics 52

Analytics Analytics Data Lakes Data Warehouse 52

Flipboard

DECEMBER 18, 2023

Amazon Redshift powers data-driven decisions for tens of thousands of customers every day with a fully managed, AI-powered cloud data warehouse, delivering the best price-performance for your analytics workloads. Learn more about the AWS zero-ETL future with newly launched AWS databases integrations with Amazon Redshift.

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phData

NOVEMBER 9, 2023

Snowflake’s Data Cloud has emerged as a leader in cloud data warehousing. As a fundamental piece of the modern data stack , Snowflake is helping thousands of businesses store, transform, and derive insights from their data easier, faster, and more efficiently than ever before.

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phData

JULY 18, 2023

With the birth of cloud data warehouses, data applications, and generative AI , processing large volumes of data faster and cheaper is more approachable and desired than ever. This typically results in long-running ETL pipelines that cause decisions to be made on stale or old data.

Data Warehouse 52

Data Warehouse Analytics Analytics SQL 52

phData

APRIL 20, 2023

In today’s world, data-driven applications demand more flexibility, scalability, and auditability, which traditional data warehouses and modeling approaches lack. This is where the Snowflake Data Cloud and data vault modeling comes in handy. What is Data Vault Modeling?

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Data Warehouse Data Governance Clustering Database 72

phData

OCTOBER 17, 2023

The story is all too common – a business user requests some data, the data team creates/prioritizes a ticket, and said ticket is completed after some number of months (or weeks if you’re lucky) – just to have the data be wrong, and the whole process starts again. Those are scary for data teams to change.

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