Analytics Vidhya

FEBRUARY 8, 2023

Introduction Amazon Redshift is a fully managed, petabyte-scale data warehousing Amazon Web Services (AWS). It allows users to easily set up, operate, and scale a data warehouse in the cloud.

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Data Warehouse AWS Analytics Analytics 306

Analytics Vidhya

DECEMBER 26, 2022

It involves extracting the operational data from various sources, transforming it into a format suitable for business needs, and loading it into data storage systems. The post Crafting Serverless ETL Pipeline Using AWS Glue and PySpark appeared first on Analytics Vidhya. Traditionally, ETL processes are […].

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ETL AWS Data Engineering Data Engineer 306

Analytics Vidhya

SEPTEMBER 27, 2022

Businesses have adopted Snowflake as migration from on-premise enterprise data warehouses (such as Teradata) or a more flexibly scalable and easier-to-manage alternative to […]. The post Data Warehousing with Snowflake and Other Alternatives appeared first on Analytics Vidhya.

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Data Warehouse Data Science Analytics Analytics 397

AWS Machine Learning Blog

DECEMBER 16, 2024

We spoke with Dr. Swami Sivasubramanian, Vice President of Data and AI, shortly after AWS re:Invent 2024 to hear his impressionsand to get insights on how the latest AWS innovations help meet the real-world needs of customers as they build and scale transformative generative AI applications. Canva uses AWS to power 1.2

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AWS AI AI Data Warehouse 105

AWS Machine Learning Blog

APRIL 3, 2025

At the heart of this transformation is the OMRON Data & Analytics Platform (ODAP), an innovative initiative designed to revolutionize how the company harnesses its data assets. The robust security features provided by Amazon S3, including encryption and durability, were used to provide data protection.

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AWS Data Governance Data Silos SQL 94

Analytics Vidhya

JANUARY 11, 2023

Introduction Amazon Elastic MapReduce (EMR) is a fully managed service that makes it easy to process large amounts of data using the popular open-source framework Apache Hadoop. EMR enables you to run petabyte-scale data warehouses and analytics workloads using the Apache Spark, Presto, and Hadoop ecosystems.

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Apache Hadoop Hadoop Data Warehouse Analytics 337

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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AWS Data Warehouse ETL SQL 139

databricks

JUNE 11, 2025

In just under 60 minutes, we had a working agent that can transform complex unstructured data usable for Analytics.” — Joseph Roemer, Head of Data & AI, Commercial IT, AstraZeneca “Agent Bricks allowed us to build a cost-effective agent we could trust in production. Agent Bricks is now available in beta.

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Analytics Analytics AI AI 237

Analytics Vidhya

FEBRUARY 19, 2023

Introduction Google’s BigQuery is a powerful cloud-based data warehouse that provides fast, flexible, and cost-effective data storage and analysis capabilities. BigQuery was created to analyse data […] The post Building a Machine Learning Model in BigQuery appeared first on Analytics Vidhya.

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Machine Learning Machine Learning Data Warehouse Database 270

Dataconomy

SEPTEMBER 4, 2023

The modern corporate world is more data-driven, and companies are always looking for new methods to make use of the vast data at their disposal. Cloud analytics is one example of a new technology that has changed the game. What is cloud analytics? How does cloud analytics work?

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Analytics Analytics Big Data Analytics Big Data Analytics 203

Data Science Dojo

JULY 6, 2023

Data engineering tools offer a range of features and functionalities, including data integration, data transformation, data quality management, workflow orchestration, and data visualization. Essential data engineering tools for 2023 Top 10 data engineering tools to watch out for in 2023 1.

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Data Engineering Data Engineering Data Engineer Data Engineering 195

databricks

JUNE 11, 2025

They sit outside the analytics and AI stack, require manual integration, and lack the flexibility needed for modern development workflows. Lakehouse integration : Lakebases should make it easy to combine operational, analytical, and AI systems without complex ETL pipelines.

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Database Data Lakes ETL Analytics 147

databricks

JUNE 11, 2025

Figure 1: Agent Bricks auto-optimizes agents for your data and task MLflow 3.0 Agents deployed on AWS, GCP, or even on-premise systems can now be connected to MLflow 3 for agent observability. Now with MLflow 3, you can monitor and observe agents that are deployed anywhere , even outside of Databricks.

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AI AI SQL Data Science 130

AWS Machine Learning Blog

OCTOBER 28, 2024

The workflow includes the following steps: Within the SageMaker Canvas interface, the user composes a SQL query to run against the GCP BigQuery data warehouse. Athena uses the Athena Google BigQuery connector , which uses a pre-built AWS Lambda function to enable Athena federated query capabilities.

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Machine Learning Machine Learning ML ML 114

IBM Journey to AI blog

OCTOBER 30, 2023

Businesses globally recognize the power of generative AI and are eager to harness data and AI for unmatched growth, sustainable operations, streamlining and pioneering innovation. In this quest, IBM and AWS have forged a strategic alliance, aiming to transition AI’s business potential from mere talk to tangible action.

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Flipboard

DECEMBER 11, 2024

Many of these applications are complex to build because they require collaboration across teams and the integration of data, tools, and services. Data engineers use data warehouses, data lakes, and analytics tools to load, transform, clean, and aggregate data.

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SQL AWS Data Lakes AI 160

AWS Machine Learning Blog

SEPTEMBER 18, 2024

ZOE is a multi-agent LLM application that integrates with multiple data sources to provide a unified view of the customer, simplify analytics queries, and facilitate marketing campaign creation. Additionally, Feast promotes feature reuse, so the time spent on data preparation is reduced greatly.

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AWS Machine Learning Machine Learning ML 128

Women in Big Data

NOVEMBER 27, 2024

A data warehouse is a centralized repository designed to store and manage vast amounts of structured and semi-structured data from multiple sources, facilitating efficient reporting and analysis. Begin by determining your data volume, variety, and the performance expectations for querying and reporting.

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Data Warehouse Big Data Big Data Azure 59

Precisely

MARCH 9, 2023

As cloud computing platforms make it possible to perform advanced analytics on ever larger and more diverse data sets, new and innovative approaches have emerged for storing, preprocessing, and analyzing information. In this article, we’ll focus on a data lake vs. data warehouse.

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Data Warehouse Data Lakes Hadoop Big Data 59

IBM Journey to AI blog

FEBRUARY 2, 2023

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights.

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Data Warehouse Cloud Data Analytics Analytics 58

IBM Journey to AI blog

MARCH 14, 2024

The solution: IBM databases on AWS To solve for these challenges, IBM’s portfolio of SaaS database solutions on Amazon Web Services (AWS), enables enterprises to scale applications, analytics and AI across the hybrid cloud landscape. Let’s delve into the database portfolio from IBM available on AWS. 

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AWS Database ETL AI 93

IBM Journey to AI blog

JUNE 2, 2023

improved document management capabilities, web portals, mobile applications, data warehouses, enhanced location services, etc.) Why IBM Consulting and AWS? AWS has the biggest cloud infrastructure services vendor market share worldwide, averaging around 33% as of Q4 2022.

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Analytics Vidhya

JANUARY 2, 2023

While not all of us are tech enthusiasts, we all have a fair knowledge of how Data Science works in our day-to-day lives. All of this is based on Data Science which is […]. The post Step-by-Step Roadmap to Become a Data Engineer in 2023 appeared first on Analytics Vidhya.

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Data Engineering Data Engineering Data Engineer Data Engineering 329

Analytics Vidhya

FEBRUARY 6, 2023

To make these processes efficient, data pipelines are necessary. Data engineers specialize in building and maintaining these data pipelines that underpin the analytics ecosystem. In this blog, we will […] The post How to Implement a Data Pipeline Using Amazon Web Services?

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Data Pipeline Data Engineering Data Engineer Data Engineering 271

Analytics Vidhya

DECEMBER 31, 2022

The post How to Encrypt and Decrypt the Data in PySpark? appeared first on Analytics Vidhya. To access services, we need to share essential details like email IDs, phone numbers, social security numbers, etc. These details can get leaked if the […].

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Data Science Analytics Analytics Data Warehouse 317

AWS Machine Learning Blog

MAY 25, 2023

This post was co-authored by Brian Curry (Founder and Head of Products at OCX Cognition) and Sandhya MN (Data Science Lead at InfoGain) OCX Cognition is a San Francisco Bay Area-based startup, offering a commercial B2B software as a service (SaaS) product called Spectrum AI. This reduced the need to develop new low-level ML code.

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AWS ML ML Data Science 95

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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Data Warehouse Cloud Data ETL Cloud Computing 52

Tableau

DECEMBER 22, 2020

We recently wrapped up participation in the all-virtual AWS re:Invent 2020 where we shared our experiences from scaling Tableau Public ten-fold this year. This includes offering broader access to data and analytics and embracing the cloud to better adapt, innovate, and grow more resilient while facing the unexpected.

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Analytics Analytics Tableau AWS 91

Analytics Vidhya

FEBRUARY 4, 2023

The transformation process occurs outside the target, a separate processing tool or […] The post Unlock the True Potential of Your Data with ETL and ELT Pipeline appeared first on Analytics Vidhya.

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ETL Analytics Analytics Data Warehouse 298

Dataversity

MAY 28, 2024

Most enterprises today store and process vast amounts of data from various sources within a centralized repository known as a data warehouse or data lake, where they can analyze it with advanced analytics tools to generate critical business insights.

Analytics 52

Analytics Analytics Data Warehouse Data Lakes 52

Analytics Vidhya

FEBRUARY 19, 2023

Overall, data pipelines are a critical component of any data-driven organization, helping to ensure […] The post Top 10 Data Pipeline Interview Questions to Read in 2023 appeared first on Analytics Vidhya.

Data Pipeline 271

Data Pipeline Analytics Analytics Data Warehouse 271

Smart Data Collective

SEPTEMBER 8, 2021

The ETL process is defined as the movement of data from its source to destination storage (typically a Data Warehouse) for future use in reports and analyzes. The data is initially extracted from a vast array of sources before transforming and converting it to a specific format based on business requirements.

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ETL Hadoop Data Warehouse Data Pipeline 126

Flipboard

AUGUST 17, 2023

Amazon Redshift is the most popular cloud data warehouse that is used by tens of thousands of customers to analyze exabytes of data every day. It provides a single web-based visual interface where you can perform all ML development steps, including preparing data and building, training, and deploying models.

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ML ML AWS Data Warehouse 123

AWS Machine Learning Blog

DECEMBER 29, 2022

You can quickly launch the familiar RStudio IDE and dial up and down the underlying compute resources without interrupting your work, making it easy to build machine learning (ML) and analytics solutions in R at scale. AWS offers tools such as RStudio on SageMaker and Amazon Redshift to help tackle these challenges. Conclusion.

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AWS Machine Learning Blog

JUNE 5, 2023

This means that business analysts who want to extract insights from the large volumes of data in their data warehouse must frequently use data stored in Parquet. Canvas provides connectors to AWS data sources such as Amazon Simple Storage Service (Amazon S3), Athena, and Amazon Redshift. Choose Grant.

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Machine Learning Machine Learning AWS Data Lakes 98

IBM Journey to AI blog

MAY 9, 2023

IBM today announced it is launching IBM watsonx.data , a data store built on an open lakehouse architecture, to help enterprises easily unify and govern their structured and unstructured data, wherever it resides, for high-performance AI and analytics. The solution will also be available in AWS Marketplace.

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Data Warehouse AWS AI AI 92

AWS Machine Learning Blog

FEBRUARY 14, 2024

Amazon Redshift has announced a feature called Amazon Redshift ML that makes it straightforward for data analysts and database developers to create, train, and apply machine learning (ML) models using familiar SQL commands in Redshift data warehouses. An SSL certificate created and imported into AWS Certificate Manager (ACM).

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AWS AI AI Database 142