Pickl AI

JULY 25, 2023

They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. With expertise in programming languages like Python , Java , SQL, and knowledge of big data technologies like Hadoop and Spark, data engineers optimize pipelines for data scientists and analysts to access valuable insights efficiently.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Mlearning.ai

MAY 23, 2023

A good course to upskill in this area is — Machine Learning Specialization Data Visualization The ability to effectively communicate insights through data visualization is important. Additionally, knowledge of model evaluation, hyperparameter tuning, and model selection is valuable.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

JULY 18, 2023

It is popular for its powerful data visualization and analysis capabilities. Hence, Data Scientists rely on R to perform complex statistical operations. With a wide array of packages like ggplot2 and dplyr, R allows for sophisticated data visualization and efficient data manipulation. Wrapping it up !!!

Data Science 52

Data Science SQL Data Scientist Python 52

Pickl AI

JULY 10, 2023

The programming language can handle Big Data and perform effective data analysis and statistical modelling. Hence, you can use R for classification, clustering, statistical tests and linear and non-linear modelling. How is R Used in Data Science? Accordingly, Caret represents regression as well as classification training.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

JANUARY 28, 2025

This layer is critical as it transforms raw data into actionable insights that drive business decisions. Data Visualization Data visualization tools present analyzed data in an easily understandable format. Prescriptive Analytics : Offers recommendations for actions based on predictive models.

Business Intelligence 52

Business Intelligence Business Intelligence ETL Data Lakes 52

ODSC - Open Data Science

JANUARY 7, 2025

Tools like Apache Airflow are widely used for scheduling and monitoring workflows, while Apache Spark dominates big data pipelines due to its speed and scalability. Hadoop, though less common in new projects, is still crucial for batch processing and distributed storage in large-scale environments.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

Pickl AI

JULY 20, 2023

Descriptive Analytics Projects: These projects focus on summarizing historical data to gain insights into past trends and patterns. Examples include generating reports, dashboards, and data visualizations to understand business performance, customer behavior, or operational efficiency.

Analytics 40

Analytics Analytics Big Data Big Data 40

Dataconomy

APRIL 16, 2025

Efficient data analysis is the backbone of successful data science projects. Hadoop: A robust framework known for efficient data processing and storage of large datasets. Spark: Excelling in large-scale data processing, it streamlines deployment across various environments.

Data Science 91

Data Science Data Mining Data Mining Data Mining 91

Dataconomy

MARCH 19, 2025

Essential technical skills Data preparation and mining: Proficiency in cleaning and organizing data effectively. Data visualization and storytelling: The ability to communicate findings clearly and effectively. Roles within a data science team Data engineer: Responsible for building and managing data pipelines.

Data Science 91

Data Science Citizen Data Scientist Data Scientist Machine Learning 91