databricks

JUNE 4, 2025

160 Spear Street, 15th Floor San Francisco, CA 94105 1-866-330-0121 See Careers at Databricks © Databricks 2025.

AWS 130

AWS AI AI Data Science 130

Pickl AI

APRIL 9, 2025

Summary: This guide explores the top list of ETL tools, highlighting their features and use cases. It provides insights into considerations for choosing the right tool, ensuring businesses can optimize their data integration processes for better analytics and decision-making. What is ETL? What are ETL Tools?

ETL 52

ETL Data Warehouse AWS Business Intelligence 52

Pickl AI

DECEMBER 15, 2024

Familiarise yourself with ETL processes and their significance. It enables organisations to perform complex queries and analyses, making it a crucial element for business intelligence and decision-making processes. ETL Process: Extract, Transform, Load processes that prepare data for analysis.

Data Warehouse 52

Data Warehouse ETL Database Data Quality 52

The MLOps Blog

MAY 17, 2023

However, efficient use of ETL pipelines in ML can help make their life much easier. This article explores the importance of ETL pipelines in machine learning, a hands-on example of building ETL pipelines with a popular tool, and suggests the best ways for data engineers to enhance and sustain their pipelines.

ETL 59

ETL Data Pipeline ML ML 59

Smart Data Collective

APRIL 29, 2020

Extraction, Transform, Load (ETL). The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Microsoft Azure. The Azure platform has a variety of tools for setting up data management systems, and analytics tools that can be applied to the stored data.

Data Warehouse 99

Data Warehouse Azure SQL ETL 99

Women in Big Data

NOVEMBER 27, 2024

Optimized for analytical processing, it uses specialized data models to enhance query performance and is often integrated with business intelligence tools, allowing users to create reports and visualizations that inform organizational strategies. Pay close attention to the cost structure, including any potential hidden fees.

Data Warehouse 59

Data Warehouse Big Data Big Data Azure 59

Dataconomy

SEPTEMBER 4, 2023

Data models help visualize and organize data, processing applications handle large datasets efficiently, and analytics models aid in understanding complex data sets, laying the foundation for business intelligence. Use ETL (Extract, Transform, Load) processes or data integration tools to streamline data ingestion.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

Data Science Blog

FEBRUARY 4, 2023

The fusion of data in a central platform enables smooth analysis to optimize processes and increase business efficiency in the world of Industry 4.0 using methods from business intelligence , process mining and data science.

Cloud Data 147

Cloud Data Data Science Business Intelligence Business Intelligence 147

Data Science Blog

JUNE 21, 2023

Cloud platforms, such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP), provide scalable and flexible infrastructure options. What makes the difference is a smart ETL design capturing the nature of process mining data. But costs won’t decrease only migrating from on-premises to cloud and vice versa.

Big Data 130

Big Data Big Data Data Engineer Data Engineering 130

ODSC - Open Data Science

JUNE 12, 2023

Then we have some other ETL processes to constantly land the past 5 years of data into the Datamarts. Then we have some other ETL processes to constantly land the past 5 years of data into the Datamarts. Power BI Datamarts provide no-code/low-code datamart capabilities using Azure SQL Database technology in the background.

Power BI 52

Power BI Data Warehouse ETL Data Preparation 52

Pickl AI

NOVEMBER 4, 2024

Enhanced Data Integration ODBC facilitates seamless data integration across platforms and applications, making it an ideal solution for business intelligence tools and reporting systems. A notable feature of this driver is its compatibility with Azure SQL Database, enabling users to connect to cloud-based SQL databases effortlessly.

Database 52

Database SQL ETL Azure 52

phData

FEBRUARY 21, 2025

A data warehouse enables advanced analytics, reporting, and business intelligence. Examples include: Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). Complex data transformations and ETL/ELT pipelines with significant data movement can see increases in latency.

Data Warehouse 52

Data Warehouse Cloud Data ETL Cloud Computing 52

Pickl AI

MARCH 19, 2025

It is commonly used for analytics and business intelligence, helping organisations make data-driven decisions. It allows businesses to store and analyse large datasets without worrying about infrastructure management. Looker : A business intelligence tool for data exploration and visualization.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

ODSC - Open Data Science

JANUARY 18, 2024

These areas may include SQL, database design, data warehousing, distributed systems, cloud platforms (AWS, Azure, GCP), and data pipelines. Microsoft Azure in particular allows users to explore the Azure ecosystem and provides on-site training for users of all levels. Learn more about the cloud.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

How to Learn Machine Learning

APRIL 26, 2025

Tools like Python (with pandas and NumPy), R, and ETL platforms like Apache NiFi or Talend are used for data preparation before analysis. AI Product Manager Manages AI-driven product development, requiring technical and business expertise. Business Intelligence (BI) Analyst Focuses on dash boarding, reporting, and KPI monitoring.

Data Science 52

Data Science Data Analyst Data Scientist Machine Learning 52

Pickl AI

MARCH 10, 2025

Summary: Power BI is a business intelligence tool that transforms raw data into actionable insights. Introduction Managing business and its key verticals can be challenging. Power BI is a powerful business intelligence tool that transforms raw data into actionable insights through interactive dashboards and reports.

Power BI 52

Power BI Business Intelligence Business Intelligence Analytics 52

IBM Journey to AI blog

JANUARY 18, 2023

Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. This adds an additional ETL step, making the data even more stale. Data platform architecture has an interesting history. It was Datawarehouse.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52

phData

SEPTEMBER 25, 2024

While numerous ETL tools are available on the market, selecting the right one can be challenging. There are a few Key factors to consider when choosing an ETL tool, which includes: Business Requirement: What type or amount of data do you need to handle? It can be hosted on major cloud platforms like AWS, Azure, and GCP.

ETL 52

ETL Database Data Warehouse Analytics 52

phData

JULY 11, 2023

Power BI Datamarts provides a low/no code experience directly within Power BI Service that allows developers to ingest data from disparate sources, perform ETL tasks with Power Query, and load data into a fully managed Azure SQL database.

Power BI 40

Power BI SQL Azure ETL 40

Pickl AI

DECEMBER 16, 2024

Data Factory : Simplifies the creation of ETL pipelines to integrate data from diverse sources. Power BI is a dynamic business intelligence and analytics platform that transforms raw data into actionable insights through powerful visualisations and reports. Power BI : Provides dynamic dashboards and reporting tools.

Power BI 52

Power BI Analytics Analytics Machine Learning 52

Pickl AI

SEPTEMBER 10, 2024

Power Query Power Query is another transformative AI tool that simplifies data extraction, transformation, and loading ( ETL ). The integration allows for seamless data connectivity between Excel and Power BI, leveraging AI to provide comprehensive business intelligence and actionable insights.

Power BI 52

Power BI Data Analysis Data Analysis AI 52

databricks

JUNE 12, 2025

Sample Dataflow Graph Declarative APIs make ETL simpler and more maintainable Through years of working with real-world Spark users, we’ve seen common challenges emerge when building production pipelines: Too much time spent wiring together pipelines with “glue code” to handle incremental ingestion or deciding when to materialize datasets.

SQL 245

SQL Data Engineer Data Engineering Data Engineering 245

DagsHub

NOVEMBER 11, 2024

These capture the semantic relationships between words, facilitating tasks like classification and clustering within ETL pipelines. Multimodal embeddings help combine unstructured data from various sources in data warehouses and ETL pipelines. The features extracted in the ETL process would then be inputted into the ML models.

AI 52

AI AI Data Lakes Database 52

Pickl AI

APRIL 26, 2024

Data Warehousing and ETL Processes What is a data warehouse, and why is it important? It is essential to provide a unified data view and enable business intelligence and analytics. Explain the Extract, Transform, Load (ETL) process. Have you worked with cloud-based data platforms like AWS, Google Cloud, or Azure?

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

phData

SEPTEMBER 19, 2023

Thankfully, there are tools available to help with metadata management, such as AWS Glue, Azure Data Catalog, or Alation, that can automate much of the process. However, this can be time-consuming and prone to human error, leading to misinformation. What are the Best Data Modeling Methodologies and Processes?

Data Lakes 52

Data Lakes Data Models Data Modeling Data Warehouse 52

phData

JULY 18, 2023

This typically results in long-running ETL pipelines that cause decisions to be made on stale or old data. Business-Focused Operation Model: Teams can shed countless hours of managing long-running and complex ETL pipelines that do not scale. It should also enable easy sharing of insights across the organization.

Data Warehouse 52

Data Warehouse Analytics Analytics Cloud Data 52

databricks

JUNE 16, 2025

160 Spear Street, 15th Floor San Francisco, CA 94105 1-866-330-0121 See Careers at Databricks © Databricks 2025. 160 Spear Street, 15th Floor San Francisco, CA 94105 1-866-330-0121 See Careers at Databricks © Databricks 2025.

Data Science 130

Data Science Artificial Intelligence Artificial Intelligence Business Intelligence 130

Flipboard

JUNE 16, 2025

Next Steps: Transition into data engineering (PySpark, ETL) or machine learning (TensorFlow, PyTorch). Cloud Computing: Platforms: Amazon Web Services (AWS), Azure, Google Cloud Skills: Docker, Kubernetes, and basic DevOps tools must be learnt to enhance employability. MySQL, PostgreSQL) and non-relational (e.g.,

Python 50

Python AWS Machine Learning Machine Learning 50