Dataconomy

MARCH 5, 2025

How descriptive analytics works Descriptive analytics utilizes statistical techniques to interpret and summarize data. By applying various methods, organizations can make findings accessible to stakeholders, ensuring that key insights lead to informed decision-making.

Analytics 91

Analytics Analytics Predictive Analytics Data Wrangling 91

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

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. For example, business analysts can use BI dashboards to conduct in-depth business analytics and visualize key performance metrics compiled from relevant datasets.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

Pickl AI

NOVEMBER 18, 2024

Who is a Data Analyst? A Data Analyst collects, processes, and interprets data to help organisations make informed decisions. They transform raw data into meaningful insights, enabling businesses to identify trends, solve problems, and strategise effectively.

Data Analyst 110

Data Analyst SQL Python AWS 110

ODSC - Open Data Science

APRIL 6, 2023

For budding data scientists and data analysts, there are mountains of information about why you should learn R over Python and the other way around. Though both are great to learn, what gets left out of the conversation is a simple yet powerful programming language that everyone in the data science world can agree on, SQL.

SQL 98

SQL Data Scientist Database Data Science 98

Pickl AI

APRIL 10, 2023

Data Analysts need deeper knowledge on SQL to understand relational databases like Oracle, Microsoft SQL and MySQL. Moreover, SQL is an important tool for conducting Data Preparation and Data Wrangling. For example, Data Analysts who need to use Big Data tools for conducting data analysis need to have expertise in SQL.

Data Analyst 52

Data Analyst SQL Data Analysis Data Analysis 52

Pickl AI

AUGUST 9, 2024

Volume It refers to the sheer amount of data generated daily, which can range from terabytes to petabytes. Organisations must develop strategies to store and manage this vast amount of information effectively. Velocity It indicates the speed at which data is generated and processed, necessitating real-time analytics capabilities.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52