How to Learn Machine Learning

APRIL 26, 2025

Data Visualization and Interpretation To make the data understandable to stakeholders, visualizations are created in the form of charts, graphs, and dashboards. Visualization libraries available in Python such as Matplotlib and Seaborn, and tools like Tableau and Power BI become crucial to telling stories that lead to insights.

Data Science 52

Data Science Data Analyst Data Scientist Machine Learning 52

Smart Data Collective

JULY 22, 2019

Microsoft Power BI. Microsoft Power BI is a free and powerful business intelligence tool from a world-leading software giant Microsoft. This BI tool allows you to get data and insights in minutes with your smartphone, tablet or laptop. It can analyze practically any size of data.

Business Intelligence 103

Business Intelligence Business Intelligence Power BI Tableau 103

Women in Big Data

DECEMBER 9, 2024

There is a plethora of BI tools available in the market today, with new ones being added yearly. Through a comparative analysis of some of the leading BI tools: Google Looker, Microsoft Power BI, Tableau and Qlik Sense, discover which BI solution best fits your organization’s data analytics needs to empower informed decision-making.

Big Data 52

Big Data Big Data Power BI Tableau 52

Pickl AI

MARCH 19, 2025

It helps data engineers collect, store, and process streams of records in a fault-tolerant way, making it crucial for building reliable data pipelines. Amazon Redshift Amazon Redshift is a cloud-based data warehouse that enables fast query execution for large datasets.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Alation

JANUARY 17, 2023

The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform. 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 Warehouse 52

Data Warehouse ETL Tableau Cloud Data 52

Pickl AI

JANUARY 15, 2025

ETL (Extract, Transform, Load) Tools ETL tools are crucial for data integration processes. They extract data from various sources, transform it into a suitable format, and load it into a target database or data warehouse for analysis.

Business Intelligence 52

Business Intelligence Business Intelligence Power BI Data Visualization 52

ODSC - Open Data Science

FEBRUARY 6, 2024

This open-source streaming platform enables the handling of high-throughput data feeds, ensuring that data pipelines are efficient, reliable, and capable of handling massive volumes of data in real-time. Each platform offers unique features and benefits, making it vital for data engineers to understand their differences.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Pickl AI

MARCH 3, 2025

Roles and Responsibilities of Business Intelligence Analyst The roles and responsibilities of a BI Analyst are diverse and can vary depending on the organization’s size and industry. Ensuring data integrity and security. Gain proficiency in data visualization tools like Tableau, Power BI, or Looker.

Business Intelligence 52

Business Intelligence Business Intelligence Data Analyst Data Visualization 52

Alation

MARCH 29, 2022

This led to the birth of separate systems for reporting: the enterprise data warehouse. For the first time, the focus of a system became business questions, where data was denormalized. These so-called “citizen data scientists” remained a roadblock between business users and data — and between data and decision making.

Business Intelligence 96

Business Intelligence Business Intelligence Data Silos Citizen Data Scientist 96

IBM Journey to AI blog

SEPTEMBER 19, 2023

To pursue a data science career, you need a deep understanding and expansive knowledge of machine learning and AI. js and Tableau Data science, data analytics and IBM Practicing data science isn’t without its challenges. Watsonx comprises of three powerful components: the watsonx.ai

Data Science 94

Data Science Analytics Analytics Data Scientist 94

phData

DECEMBER 12, 2023

Step 2: Analyze the Data Once you have centralized your data, use a business intelligence tool like Sigma Computing , Power BI , Tableau , or another to craft analytics dashboards. We are going to break down what we know about Victory Vicky based on all the data sources we have moved into our data warehouse.

Data Warehouse 52

Data Warehouse Machine Learning Machine Learning Tableau 52

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 70

Business Intelligence Business Intelligence Data Analysis Data Analysis 70

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 70

Business Intelligence Business Intelligence Data Analysis Data Analysis 70

phData

FEBRUARY 9, 2023

One popular option is the Snowflake Data Cloud , a cloud-based data warehouse that allows users to store, query, and analyze large amounts of data.

Analytics 52

Analytics Analytics Power BI Data Warehouse 52

Pickl AI

JANUARY 28, 2025

This involves several key processes: Extract, Transform, Load (ETL): The ETL process extracts data from different sources, transforms it into a suitable format by cleaning and enriching it, and then loads it into a data warehouse or data lake. Data Lakes: These store raw, unprocessed data in its original format.

Business Intelligence 52

Business Intelligence Business Intelligence ETL Data Lakes 52

Pickl AI

JULY 3, 2023

Here are steps you can follow to pursue a career as a BI Developer: Acquire a solid foundation in data and analytics: Start by building a strong understanding of data concepts, relational databases, SQL (Structured Query Language), and data modeling.

Business Intelligence 52

Business Intelligence Business Intelligence SQL Data Visualization 52

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 52

Data Warehouse Data Quality ETL Business Intelligence 52

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 52

Data Quality Data Warehouse Data Governance Analytics 52

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 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Pickl AI

JULY 25, 2023

Data Visualization: Matplotlib, Seaborn, Tableau, etc. Big Data Technologies: Hadoop, Spark, etc. Domain Knowledge: Understanding the specific domain where they apply data analysis. They work with databases and data warehouses to ensure data integrity and security.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

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 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

Data Science Blog

FEBRUARY 7, 2023

Vor einen Jahrzehnt war es immer noch recht üblich, sich einfach ein BI Tool zu nehmen, sowas wie QlikView, Tableau oder PowerBI, mittlerweile gibt es ja noch einige mehr, und da direkt die Daten reinzuladen und dann halt loszulegen mit dem Aufbau der Reports. Ein Data Warehouse ist eine oder eine Menge von Datenbanken.

Business Intelligence 286

Business Intelligence Business Intelligence Data Warehouse Data Lakes 286

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 130

Azure SQL Power BI Data Lakes 130