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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Dataconomy

SEPTEMBER 4, 2023

Cloud analytics is the art and science of mining insights from data stored in cloud-based platforms. By tapping into the power of cloud technology, organizations can efficiently analyze large datasets, uncover hidden patterns, predict future trends, and make informed decisions to drive their businesses forward.

Analytics 203

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phData

FEBRUARY 21, 2025

In this post, we will be particularly interested in the impact that cloud computing left on the modern data warehouse. We will explore the different options for data warehousing and how you can leverage this information to make the right decisions for your organization. Understanding the Basics What is a Data Warehouse?

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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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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, a cloud-based automated data integration platform, has emerged as a leading choice among businesses looking for an easy and cost-effective way to unify their data from various sources. It allows organizations to easily connect their disparate data sources without having to manage any infrastructure.

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Smart Data Collective

OCTOBER 17, 2022

While growing data enables companies to set baselines, benchmarks, and targets to keep moving ahead, it poses a question as to what actually causes it and what it means to your organization’s engineering team efficiency. What’s causing the data explosion? Big data analytics from 2022 show a dramatic surge in information consumption.

Big Data 119

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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. Why Does This Matter?

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Precisely

APRIL 3, 2023

Whether you’re a financial services company using data to combat financial crime, a transportation company seeking to minimize your climate impact, or a manufacturing business aiming to optimize your supply chain, digital modernization provides critical insights and visibility, unlocking the information critical to your success.

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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.

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How to Learn Machine Learning

APRIL 26, 2025

Data Cleaning and Preparation The tasks of cleaning and preparing the data take place before the analysis. This includes duplicate removal, missing value treatment, variable transformation, and normalization of data.

Data Science 52

Data Science Data Analyst Data Scientist Machine Learning 52

phData

APRIL 28, 2025

A Matillion pipeline is a collection of jobs that extract, load, and transform (ETL/ELT) data from various sources into a target system, such as a cloud data warehouse like Snowflake. The workflow well reference throughout this blog was built using customer data from TrellisMart, a fictional retail company.

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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.

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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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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. Every company’s path to data integrity is unique and should be driven by the organization’s strategic priorities. To learn more, read our ebook.

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Alation

OCTOBER 19, 2021

What Are Data Silos? Data silos, also called information silos, are pockets of information stored in different information systems or subsystems that don’t connect with one another. If your company is collecting and storing a lot of data in different locations, there’s a good chance you have a data silo.

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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.

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Dataversity

MARCH 12, 2024

While we haven’t built technology that enables real-time matter transfer yet, modern science is pursuing concepts like superposition and quantum teleportation to facilitate information transfer across any distance […] The post 10 Advantages of Real-Time Data Streaming in Commerce appeared first on DATAVERSITY.

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phData

APRIL 20, 2023

Including business vault tables in the raw vault is not mandatory, as a compliant data vault can be created without them. Information Mart The information mart is the final stage, where the data is optimized for analysis and reporting. By combining the Snowflake Data Cloud with a Data Vault 2.0

Data Warehouse 72

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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 52

Data Governance ETL Data Pipeline Azure 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

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IBM Journey to AI blog

JULY 17, 2023

These encoder-only architecture models are fast and effective for many enterprise NLP tasks, such as classifying customer feedback and extracting information from large documents. While they require task-specific labeled data for fine tuning, they also offer clients the best cost performance trade-off for non-generative use cases.

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AI AI Machine Learning Machine Learning 74

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.

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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

Walking you through the biggest challenges we have found when migrating our customer’s data from a legacy system to Snowflake. Background Information on Migrating to Snowflake So you’ve decided to move from your current data warehousing solution to Snowflake, and you want to know what challenges await you.

SQL 52

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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. What Are Alerts in Snowflake? daily or weekly).

SQL 52

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Alation

APRIL 4, 2023

Now, joint users will get an enhanced view into cloud and data transformations , with valuable context to guide smarter usage. At the heart of this release is the need to empower people with the right information at the right time. To build effective data pipelines, they need context (or metadata) on every source.

DataOps 52

DataOps Data Engineer Data Engineering Data Engineering 52

phData

FEBRUARY 14, 2023

This may result in data inconsistency when UPDATE and DELETE operations are performed on the target database. It’s a code-free wizard that provides basic administration capabilities like controlling access to pipelines, connections to data source endpoint, and cloud data warehouse.

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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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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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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

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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. This produces end-to-end lineage so business and technology users alike can understand the state of a data lake and/or lake house.

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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.

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Dataversity

APRIL 8, 2021

Business intelligence (BI) tools transform the unprocessed data into meaningful and actionable insight. BI tools analyze the data and convert them […]. Click to learn more about author Piyush Goel. What is a BI tool? Which BI tool is best for your organization?

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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.

SQL 52

SQL Data Warehouse Analytics Analytics 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

JUNE 7, 2022

Unlocking value from data is a journey. It involves investing in data infrastructure, analysts, scientists, and processes for managing data consumption. Even when data operations teams progress along this journey, growing pains crop up as more users want more data. You don’t have to grin […].

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