Data Science Dojo

OCTOBER 31, 2024

Key Skills Proficiency in SQL is essential, along with experience in data visualization tools such as Tableau or Power BI. Additionally, knowledge of cloud platforms (AWS, Google Cloud) and experience with deployment tools (Docker, Kubernetes) are highly valuable.

Data Science 195

Data Science Data Scientist Machine Learning Machine Learning 195

Pickl AI

DECEMBER 25, 2024

Dashboards, such as those built using Tableau or Power BI , provide real-time visualizations that help track key performance indicators (KPIs). Big data platforms such as Apache Hadoop and Spark help handle massive datasets efficiently. Data Scientists require a robust technical foundation.

Data Science 52

Data Science Analytics Analytics Data Scientist 52

Data Science Dojo

JULY 3, 2024

Tools like Tableau, Power BI, and Python libraries such as Matplotlib and Seaborn are commonly taught. Big Data Technologies : Handling and processing large datasets using tools like Hadoop, Spark, and cloud platforms such as AWS and Google Cloud. R : Often used for statistical analysis and data visualization.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

Pickl AI

JANUARY 12, 2025

To confirm seamless integration, you can use tools like Apache Hadoop, Microsoft Power BI, or Snowflake to process structured data and Elasticsearch or AWS for unstructured data. Unify Data Sources Collect data from multiple systems into one cohesive dataset.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence AI AI 52

Mlearning.ai

MARCH 15, 2023

Experience with cloud platforms like; AWS, AZURE, etc. Experience with visualization tools like; Tableau and Power BI. Knowledge of big data platforms like; Hadoop and Apache Spark. High proficiency in visualization tools like; Tableau, Google Studio, and Power BI. Basic programming knowledge in R or Python.

Data Science 52

Data Science Analytics Analytics Data Analyst 52

Pickl AI

JULY 25, 2023

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. Big Data Technologies: Hadoop, Spark, etc. Big Data Processing: Apache Hadoop, Apache Spark, etc.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

ODSC - Open Data Science

JANUARY 7, 2025

From development environments like Jupyter Notebooks to robust cloud-hosted solutions such as AWS SageMaker, proficiency in these systems is critical. 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