Analytics Vidhya

JULY 1, 2024

It serves as the primary means for communicating with relational databases, where most organizations store crucial data. SQL plays a significant role including analyzing complex data, creating data pipelines, and efficiently managing data warehouses. appeared first on Analytics Vidhya.

SQL 316

SQL Data Warehouse Data Pipeline Database 316

Analytics Vidhya

JUNE 15, 2022

Azure Data Factory […]. The post Building an ETL Data Pipeline Using Azure Data Factory appeared first on Analytics Vidhya. It helps organizations across the globe in planning marketing strategies and making critical business decisions.

ETL 270

ETL Data Pipeline Azure Data Science 270

AWS Machine Learning Blog

OCTOBER 24, 2024

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse service that makes it cost-effective to efficiently analyze all your data using your existing business intelligence tools. Amazon QuickSight powers data-driven organizations with unified (BI) at hyperscale. A SageMaker domain.

Data Warehouse 110

Data Warehouse Machine Learning Machine Learning Cloud Data 110

Smart Data Collective

SEPTEMBER 23, 2020

The market for data warehouses is booming. While there is a lot of discussion about the merits of data warehouses, not enough discussion centers around data lakes. We talked about enterprise data warehouses in the past, so let’s contrast them with data lakes. Data Warehouse.

Data Lakes 135

Data Lakes Data Warehouse Big Data Big Data 135

Smart Data Collective

OCTOBER 17, 2022

Data pipelines automatically fetch information from various disparate sources for further consolidation and transformation into high-performing data storage. There are a number of challenges in data storage , which data pipelines can help address. The movement of data in a pipeline from one point to another.

Data Pipeline 145

Data Pipeline Data Warehouse ETL Exploratory Data Analysis 145

Data Science Dojo

JULY 6, 2023

Data engineering tools are software applications or frameworks specifically designed to facilitate the process of managing, processing, and transforming large volumes of data. Essential data engineering tools for 2023 Top 10 data engineering tools to watch out for in 2023 1.

Data Engineer 195

Data Engineer Data Engineering Data Engineering Data Engineering 195

Analytics Vidhya

APRIL 3, 2023

Real-time dashboards such as GCP provide strong data visualization and actionable information for decision-makers. Nevertheless, setting up a streaming data pipeline to power such dashboards may […] The post Data Engineering for Streaming Data on GCP appeared first on Analytics Vidhya.

Data Engineer 319

Data Engineer Data Engineering Data Engineering Data Engineering 319

Data Science Dojo

SEPTEMBER 11, 2024

Microsoft Fabric aims to reduce unnecessary data replication, centralize storage, and create a unified environment with its unique data fabric method. Microsoft Fabric is a cutting-edge analytics platform that helps data experts and companies work together on data projects. What is Microsoft Fabric?

Power BI 238

Power BI Data Pipeline Data Warehouse Data Engineering 238

Smart Data Collective

OCTOBER 27, 2021

An interactive analytics application gives users the ability to run complex queries across complex data landscapes in real-time: thus, the basis of its appeal. Interactive analytics applications present vast volumes of unstructured data at scale to provide instant insights. Why Use an Interactive Analytics Application?

Analytics 130

Analytics Analytics Data Warehouse Business Intelligence 130

Analytics Vidhya

FEBRUARY 17, 2023

Through these webinars, you’ll gain hands-on experience, deepen your understanding […] The post Join DataHour Sessions With Industry Experts appeared first on Analytics Vidhya.

Analytics 319

Analytics Analytics Data Pipeline Data Warehouse 319

Alation

MAY 16, 2023

A McKinsey survey found that companies that use customer analytics intensively are 19 times higher to achieve above-average profitability. But with the sheer amount of data continually increasing, how can a business make sense of it? Robust data pipelines. What is a Data Pipeline? The answer?

Data Pipeline 69

Data Pipeline Data Governance Data Lakes Data Warehouse 69

IBM Data Science in Practice

JANUARY 13, 2025

The blog post explains how the Internal Cloud Analytics team leveraged cloud resources like Code-Engine to improve, refine, and scale the data pipelines. Background One of the Analytics teams tasks is to load data from multiple sources and unify it into a data warehouse.

ETL 100

ETL Data Pipeline Database Data Warehouse 100

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.

Data Warehouse 59

Data Warehouse Big Data Big Data Azure 59

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.

ETL 126

ETL Hadoop Data Warehouse Data Pipeline 126

Analytics Vidhya

JUNE 28, 2022

. “Preponderance data opens doorways to complex and Avant analytics.” ” Introduction to SQL Queries Data is the premium product of the 21st century. Enterprises are focused on data stockpiling because more data leads to meticulous and calculated decision-making and opens more doors for business […].

SQL 270

SQL Data Science Analytics Analytics 270

Pickl AI

JULY 8, 2024

Summary: This blog explains how to build efficient data pipelines, detailing each step from data collection to final delivery. Introduction Data pipelines play a pivotal role in modern data architecture by seamlessly transporting and transforming raw data into valuable insights.

Data Pipeline 52

Data Pipeline Data Quality Database Apache Kafka 52

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?

Data Warehouse 52

Data Warehouse Cloud Data ETL Cloud Computing 52

Analytics Vidhya

FEBRUARY 20, 2023

Azure data factory helps organizations across the globe in making critical business decisions by collecting data from various sources such as e-commerce websites, supply chains, logistics, […] The post Most Frequently Asked Azure Data Factory Interview Questions appeared first on Analytics Vidhya.

Azure 283

Azure ETL Analytics Analytics 283

IBM Journey to AI blog

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

The MLOps Blog

MAY 17, 2023

We also discuss different types of ETL pipelines for ML use cases and provide real-world examples of their use to help data engineers choose the right one. What is an ETL data pipeline in ML? Xoriant It is common to use ETL data pipeline and data pipeline interchangeably.

ETL 59

ETL Data Pipeline ML ML 59

Tableau

JUNE 8, 2021

Domain experts, for example, feel they are still overly reliant on core IT to access the data assets they need to make effective business decisions. In all of these conversations there is a sense of inertia: Data warehouses and data lakes feel cumbersome and data pipelines just aren't agile enough.

Tableau 102

Tableau Data Lakes Data Warehouse SQL 102

Dataconomy

JULY 29, 2024

Ed explained the differences between ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) processes, highlighting the advantages of the ELT approach in modern data environments. He introduced Airflow as a robust tool for orchestrating data pipelines and DBT for data transformation within data warehouses.

Apache Kafka 91

Apache Kafka Data Pipeline Data Warehouse ETL 91

IBM Journey to AI blog

OCTOBER 22, 2024

Leaders feel the pressure to infuse their processes with artificial intelligence (AI) and are looking for ways to harness the insights in their data platforms to fuel this movement. Indeed, IDC has predicted that by the end of 2024, 65% of CIOs will face pressure to adopt digital tech , such as generative AI and deep analytics.

Data Silos 102

Data Silos Data Pipeline DataOps Business Intelligence 102

Alation

MAY 16, 2023

A McKinsey survey found that companies that use customer analytics intensively are 19 times higher to achieve above-average profitability. But with the sheer amount of data continually increasing, how can a business make sense of it? Robust data pipelines. What is a Data Pipeline? The answer?

Data Pipeline 40

Data Pipeline Data Governance Data Lakes Data Warehouse 40

phData

MARCH 8, 2023

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. Fivetran is used by businesses to centralize data from various sources into a single, comprehensive data warehouse. What is Fivetran Used For? Why Use Fivetran?

Data Warehouse 96

Data Warehouse Data Engineering Data Engineering Data Engineering 96

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 […].

Analytics 69

Analytics Analytics Data Silos Data Lakes 69

phData

MAY 25, 2023

How to Optimize Power BI and Snowflake for Advanced Analytics Spencer Baucke May 25, 2023 The world of business intelligence and data modernization has never been more competitive than it is today. Much of what is discussed in this guide will assume some level of analytics strategy has been considered and/or defined. No problem!

Power BI 84

Power BI Analytics Analytics Azure 84

phData

JANUARY 5, 2023

On-Premises to The Cloud This type of migration involves moving an organization’s BI platform from an on-premises environment (such as a local server or data center) to a cloud-based environment. Learn about phData’s Elastic Platform Operations for fully managing your analytics.

Analytics 52

Analytics Analytics Tableau Database 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.

Data Warehouse 52

Data Warehouse Data Pipeline Cloud Data ETL 52

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. AWS Glue is a serverless data integration service that makes it easy to discover, prepare, and combine data for analytics, ML, and application development.

ML 123

ML ML AWS Data Warehouse 123

Women in Big Data

OCTOBER 9, 2024

The success of any data initiative hinges on the robustness and flexibility of its big data pipeline. What is a Data Pipeline? A traditional data pipeline is a structured process that begins with gathering data from various sources and loading it into a data warehouse or data lake.

Big Data 59

Big Data Big Data Apache Kafka Data Pipeline 59

phData

SEPTEMBER 5, 2023

Google Analytics 4 (GA4) is a powerful tool for collecting and analyzing website and app data that many businesses rely heavily on to make informed business decisions. However, there might be instances where you need to migrate the raw event data from GA4 to Snowflake for more in-depth analysis and business intelligence purposes.

Azure 52

Azure Analytics Analytics Data Pipeline 52

Tableau

DECEMBER 7, 2022

But good data—and actionable insights—are hard to get. Traditionally, organizations built complex data pipelines to replicate data. Those data architectures were brittle, complex, and time intensive to build and maintain, requiring data duplication and bloated data warehouse investments.

Tableau 98

Tableau Data Warehouse Data Pipeline Data Visualization 98

Tableau

DECEMBER 7, 2022

But good data—and actionable insights—are hard to get. Traditionally, organizations built complex data pipelines to replicate data. Those data architectures were brittle, complex, and time intensive to build and maintain, requiring data duplication and bloated data warehouse investments.

Tableau 98

Tableau Data Warehouse Data Pipeline Data Visualization 98

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

Big Data Big Data Data Engineering Data Engineering 119

ODSC - Open Data Science

APRIL 4, 2024

Data Analytics in the Age of AI, When to Use RAG, Examples of Data Visualization with D3 and Vega, and ODSC East Selling Out Soon Data Analytics in the Age of AI Let’s explore the multifaceted ways in which AI is revolutionizing data analytics, making it more accessible, efficient, and insightful than ever before.

Data Visualization 52

Data Visualization Analytics Analytics Big Data Analytics 52

Pickl AI

NOVEMBER 4, 2024

Data Engineering is designing, constructing, and managing systems that enable data collection, storage, and analysis. It involves developing data pipelines that efficiently transport data from various sources to storage solutions and analytical tools. ETL is vital for ensuring data quality and integrity.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52