phData

JULY 11, 2023

Power BI Datamarts is one of the most exciting features that Microsoft has released for the Power Platform in recent years. If you need high-level information on what a Power BI Datamart is and some example use cases, check out our other blog, What Are Power BI Datamarts?

Power BI 40

Power BI SQL Azure ETL 40

Towards AI

APRIL 2, 2024

Steps Involved in the Data Analysis Process (General Steps to Follow as a Data Analyst) Gather the data in any spreadsheet or database and gain a basic understanding of the data that you have using any statistical techniques or by writing SQL Queries. We have many tools that offer features like ETL, Visualization, and validations.

Data Analysis 102

Data Analysis Data Analysis Data Analyst Power BI 102

Data Science Dojo

JULY 3, 2024

Tools like Tableau, Power BI, and Python libraries such as Matplotlib and Seaborn are commonly taught. Databases and SQL : Managing and querying relational databases using SQL, as well as working with NoSQL databases like MongoDB. R : Often used for statistical analysis and data visualization.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

ODSC - Open Data Science

APRIL 6, 2023

It’s a foundational skill for working with relational databases Just about every data scientist or analyst will have to work with relational databases in their careers. Another boon for efficient work that SQL provides is its simple and consistent syntax that allows for collaboration across multiple databases.

SQL 98

SQL Data Scientist Database Data Science 98

Dataconomy

JULY 28, 2023

Here are some of the best data preprocessing tools of 2023: Microsoft Power BI Tableau Trifacta Talend Toad Data Point Power Query Microsoft Power BI Microsoft Power BI is a comprehensive data preparation tool that allows users to create reports with multiple complex data sources.

Power BI 91

Power BI Data Preparation Exploratory Data Analysis Machine Learning 91

Mlearning.ai

AUGUST 10, 2023

The project I did to land my business intelligence internship — CAR BRAND SEARCH ETL PROCESS WITH PYTHON, POSTGRESQL & POWER BI 1. Section 2: Explanation of the ETL diagram for the project. ETL ARCHITECTURE DIAGRAM ETL stands for Extract, Transform, Load. Figure 3: Car Brand search ETL diagram 2.1.

Business Intelligence 52

Business Intelligence Business Intelligence ETL Power BI 52

Pickl AI

JANUARY 15, 2025

The primary functions of BI tools include: Data Collection: Gathering data from multiple sources including internal databases, external APIs, and cloud services. They employ techniques from statistics, Machine Learning, and database systems to reveal insights that can inform strategic decisions.

Business Intelligence 52

Business Intelligence Business Intelligence Power BI Data Visualization 52

Smart Data Collective

MAY 20, 2019

With databases, for example, choices may include NoSQL, HBase and MongoDB but its likely priorities may shift over time. The popular tools, on the other hand, include Power BI, ETL, IBM Db2, and Teradata. But no matter how difficult it is, data analysts must continue to stay at the forefront of that growth.

Analytics 111

Analytics Analytics Data Analyst Machine Learning 111

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. Proficiency in SQL Server, Oracle, or MySQL is often required.

Business Intelligence 52

Business Intelligence Business Intelligence SQL Data Visualization 52

Pickl AI

MARCH 3, 2025

Essentially, BI bridges the gap between raw data and actionable knowledge. It gathers information from various sources sales databases, marketing platforms, customer feedback, and more and consolidates it into a unified view. Technical Skill Development Master SQL for database querying and manipulation.

Business Intelligence 52

Business Intelligence Business Intelligence Data Analyst Data Visualization 52

ODSC - Open Data Science

APRIL 3, 2023

Data Wrangling: Data Quality, ETL, Databases, Big Data The modern data analyst is expected to be able to source and retrieve their own data for analysis. Competence in data quality, databases, and ETL (Extract, Transform, Load) are essential. As you see, there are a number of reporting platforms as expected.

Analytics 52

Analytics Analytics Data Analyst Data Science 52

Pickl AI

JANUARY 28, 2025

They encompass all the origins from which data is collected, including: Internal Data Sources: These include databases, enterprise resource planning (ERP) systems, customer relationship management (CRM) systems, and flat files within an organization. databases), semi-structured (e.g., Data can be structured (e.g.,

Business Intelligence 52

Business Intelligence Business Intelligence ETL Data Lakes 52

Dataconomy

MARCH 24, 2023

Some of the common career opportunities in BI include: Entry-level roles Data analyst:  A data analyst is responsible for collecting and analyzing data, creating reports, and presenting insights to stakeholders. They may also be involved in data modeling and database design.

Business Intelligence 70

Business Intelligence Business Intelligence Data Analysis Data Analysis 70

Dataconomy

MARCH 24, 2023

Some of the common career opportunities in BI include: Entry-level roles Data analyst:  A data analyst is responsible for collecting and analyzing data, creating reports, and presenting insights to stakeholders. They may also be involved in data modeling and database design.

Business Intelligence 70

Business Intelligence Business Intelligence Data Analysis Data Analysis 70

Alation

JANUARY 17, 2023

Reverse ETL tools. Business intelligence (BI) platforms. The modern data stack is also the consequence of a shift in analysis workflow, fromextract, transform, load (ETL) to extract, load, transform (ELT). A Note on the Shift from ETL to ELT. In the past, data movement was defined by ETL: extract, transform, and load.

Data Warehouse 52

Data Warehouse ETL Tableau Cloud Data 52

Pickl AI

JULY 25, 2023

They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. Their primary responsibilities include: Data Collection and Preparation Data Scientists start by gathering relevant data from various sources, including databases, APIs, and online platforms. ETL Tools: Apache NiFi, Talend, etc.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Pickl AI

AUGUST 9, 2024

ETL Tools Extract, Transform, Load (ETL) tools like Talend, Informatica, and Apache Nifi enable the integration and transformation of data from source systems into the dimensional model, ensuring that hierarchies are populated correctly.

Data Warehouse 52

Data Warehouse Data Quality ETL Business Intelligence 52

DataSeries

AUGUST 15, 2024

Knowledge of Core Data Engineering Concepts Ensure one possess a strong foundation in core data engineering concepts, which include data structures, algorithms, database management systems, data modeling , data warehousing , ETL (Extract, Transform, Load) processes, and distributed computing frameworks (e.g., Hadoop, Spark).

Data Engineering 40

Data Engineering Data Engineering Data Engineering Data Engineer 40

Pickl AI

AUGUST 9, 2024

Variety It encompasses the different types of data, including structured data (like databases), semi-structured data (like XML), and unstructured formats (such as text, images, and videos). Understanding the differences between SQL and NoSQL databases is crucial for students. js for creating interactive visualisations.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Pickl AI

APRIL 26, 2024

SQL stands for Structured Query Language, essential for querying and manipulating data stored in relational databases. The SELECT statement retrieves data from a database, while SELECT DISTINCT eliminates duplicate rows from the result set. Data Warehousing and ETL Processes What is a data warehouse, and why is it important?

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

Pickl AI

AUGUST 11, 2024

ETL Tools Informatica, Talend, and Apache Airflow enable the extraction of data from source systems, transformation into the desired format, and loading into the dimensional model. These tools help streamline the design process and ensure consistency. These tools are essential for populating fact tables with accurate and timely data.

Data Quality 52

Data Quality Data Warehouse Data Governance Analytics 52

Pickl AI

JULY 18, 2024

Introduction MongoDB is a robust NoSQL database, crucial in today’s data-driven tech industry. MongoDB is a NoSQL database that handles large-scale data and modern application requirements. Unlike traditional relational databases, MongoDB stores data in flexible, JSON-like documents, allowing for dynamic schemas.

Database 52

Database SQL Data Analyst Database Administration 52

Pickl AI

MARCH 19, 2025

A data engineer creates and manages the pipelines that transfer data from different sources to databases or cloud storage. Data Storage : Keeping data safe in databases or cloud platforms. It allows them to retrieve, manipulate, and manage structured data in relational databases. What Does a Data Engineer Do?

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52