Data Warehouse, ETL and Tableau - Data Science Current

CI/CD for Data Pipelines: A Game-Changer with AnalyticsCreator

Data Science Blog

MAY 20, 2024

Enter AnalyticsCreator AnalyticsCreator, a powerful tool for data management, brings a new level of efficiency and reliability to the CI/CD process. It offers full BI-Stack Automation, from source to data warehouse through to frontend. It supports a holistic data model, allowing for rapid prototyping of various models.

Data Pipeline

Data Pipeline Data Warehouse Azure Data Lakes

Essential data engineering tools for 2023: Empowering for management and analysis

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

Data Engineer Data Engineering Data Engineering Data Engineering

CI/CD für Datenpipelines – Ein Game-Changer mit AnalyticsCreator

Data Science Blog

JULY 20, 2024

Es bietet vollständige Automatisierung des BI-Stacks und unterstützt ein breites Spektrum an Data Warehouses, analytischen Datenbanken und Frontends. Automatisierung: Erstellt SQL-Code, DACPAC-Dateien, SSIS-Pakete, Data Factory-ARM-Vorlagen und XMLA-Dateien. Data Lakes: Unterstützt MS Azure Blob Storage.

Azure

Azure Power BI SQL Data Lakes

Webinars

Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

Marketing Operations in 2025: A New Framework for Success

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Unlock the value of your Azure data with Tableau

Tableau

MARCH 30, 2021

In Tableau 2021.1, we’ve added new connectors to help our customers access more data in Azure than ever before: an Azure SQL Database connector and an Azure Data Lake Storage Gen2 connector. As our customers increasingly adopt the cloud, we continue to make investments that ensure they can access their data anywhere.

Azure

Azure Tableau Data Lakes SQL

Unlock the value of your Azure data with Tableau

Tableau

MARCH 29, 2021

In Tableau 2021.1, we’ve added new connectors to help our customers access more data in Azure than ever before: an Azure SQL Database connector and an Azure Data Lake Storage Gen2 connector. As our customers increasingly adopt the cloud, we continue to make investments that ensure they can access their data anywhere.

Azure

Azure Tableau Data Lakes SQL

The Modern Data Stack Explained: What The Future Holds

Alation

JANUARY 17, 2023

It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse. Data ingestion/integration services. Reverse ETL tools. Data orchestration tools. A Note on the Shift from ETL to ELT.

Data Warehouse

Data Warehouse ETL Tableau Cloud Data

Navigating the Big Data Frontier: A Guide to Efficient Handling

Women in Big Data

OCTOBER 9, 2024

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. Once ingested, the data is prepared through filtering, error correction, and restructuring for ease of use.

Big Data

Big Data Big Data Apache Kafka Data Pipeline

Considerations and Approaches to Loading Reference Data into Snowflake

phData

AUGUST 9, 2024

Typically, this data is scattered across Excel files on business users’ desktops. It is extremely labor intensive, and the team wants to automate it using Snowflake and Tableau. Financial data is pulled from the ERP. Snowflake can not natively read files on these services, so an ETL service is needed to upload the data.

ETL

ETL Data Warehouse Data Governance Azure

Hierarchies in Dimensional Modelling

Pickl AI

AUGUST 9, 2024

Real-world Examples To illustrate the practical applications of hierarchies in dimensional modelling, this section explores real-world examples across various industries, showcasing how hierarchies enhance data organisation, analysis, and decision-making.

Data Warehouse

Data Warehouse Data Quality Business Intelligence ETL

The Data Dilemma: Exploring the Key Differences Between Data Science and Data Engineering

Pickl AI

JULY 25, 2023

Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. Data Visualization: Matplotlib, Seaborn, Tableau, etc.

Data Engineer

Data Engineer Data Engineering Data Engineering Data Engineering

What Are The Best Third-Party Data Ingestion Tools For Snowflake?

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.

Data Warehouse

Data Warehouse Azure AWS Database

Who is a BI Developer: Role, Responsibilities & Skills

Pickl AI

JULY 3, 2023

Familiarize yourself with data analysis techniques and tools. Learn BI technologies: Gain proficiency in popular BI tools and technologies such as Microsoft Power BI, Tableau, QlikView, or MicroStrategy. BI Developer Skills Required To excel in this role, BI Developers need to possess a range of technical and soft skills.

Business Intelligence

Business Intelligence Business Intelligence SQL Data Visualization

From zero to BI hero: Launching your business intelligence career

Dataconomy

MARCH 24, 2023

They may also be involved in data modeling and database design. BI developer: A BI developer is responsible for designing and implementing BI solutions, including data warehouses, ETL processes, and reports. They may also be involved in data integration and data quality assurance.

Business Intelligence

Business Intelligence Business Intelligence Data Analysis Data Analysis

From zero to BI hero: Launching your business intelligence career

Dataconomy

MARCH 24, 2023

They may also be involved in data modeling and database design. BI developer: A BI developer is responsible for designing and implementing BI solutions, including data warehouses, ETL processes, and reports. They may also be involved in data integration and data quality assurance.

Business Intelligence

Business Intelligence Business Intelligence Data Analysis Data Analysis

Top 50+ Data Analyst Interview Questions & Answers

Pickl AI

APRIL 26, 2024

Data Warehousing and ETL Processes What is a data warehouse, and why is it important? A data warehouse is a centralised repository that consolidates data from various sources for reporting and analysis. It is essential to provide a unified data view and enable business intelligence and analytics.

Data Analyst

Data Analyst Data Analysis Data Analysis Machine Learning

Best Practices for Fact Tables in Dimensional Models

Pickl AI

AUGUST 11, 2024

Retail Sales In a retail data warehouse , the sales fact table might include metrics such as sales revenue, units sold, discounts applied, and profit margins. Web Analytics In a web analytics data warehouse, the page views fact table might include metrics such as total page views, unique visitors, session duration, and bounce rate.

Data Quality

Data Quality Data Warehouse Data Governance Business Intelligence

Big Data Syllabus: A Comprehensive Overview

Pickl AI

AUGUST 9, 2024

Data Warehousing Solutions Tools like Amazon Redshift, Google BigQuery, and Snowflake enable organisations to store and analyse large volumes of data efficiently. Students should learn about the architecture of data warehouses and how they differ from traditional databases. js for creating interactive visualisations.

Big Data

Big Data Big Data Big Data Analytics Big Data Analytics

What are the Biggest Challenges with Migrating to Snowflake?

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

SQL Database Data Quality Data Warehouse

What Is a Data Fabric and How Does a Data Catalog Support It?

Alation

JANUARY 25, 2022

This will allow them to be certain it’s the data they need, at which point they can use their data prep or pipeline tools against the actual source to continue with the development phase of their work. Alation partners such as Dataiku, Trifacta, and Tableau are perfect examples.

DataOps

DataOps SQL ML ML