Pickl AI

AUGUST 9, 2024

Some of the most notable technologies include: Hadoop An open-source framework that allows for distributed storage and processing of large datasets across clusters of computers. It is built on the Hadoop Distributed File System (HDFS) and utilises MapReduce for data processing. js for creating interactive visualisations.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 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. These models may include regression, classification, clustering, and more.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Pickl AI

JULY 10, 2023

Hence, you can use R for classification, clustering, statistical tests and linear and non-linear modelling. Packages like caret, random Forest, glmnet, and xgboost offer implementations of various machine learning algorithms, including classification, regression, clustering, and dimensionality reduction. How is R Used in Data Science?

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

JANUARY 28, 2025

By consolidating data from over 10,000 locations and multiple websites into a single Hadoop cluster, Walmart can analyse customer purchasing trends and optimize inventory management. Walmart Walmart has implemented a robust BI architecture to manage data from its extensive network of stores and online platforms.

Business Intelligence 52

Business Intelligence Business Intelligence ETL Data Lakes 52

Pickl AI

MAY 29, 2024

Knowledge of supervised and unsupervised learning and techniques like clustering, classification, and regression is essential. Proficiency with tools like Tableau , Matplotlib , and ggplot2 helps create charts, graphs, and dashboards that effectively communicate insights to stakeholders.

Data Scientist 52

Data Scientist Data Science Machine Learning Machine Learning 52

Pickl AI

MARCH 10, 2023

It contains data clustering, classification, anomaly detection and time-series forecasting. Some of the tools used by Data Science in 2023 include statistical analysis system (SAS), Apache, Hadoop, and Tableau. Some of the best tools and techniques for applying Data Science include Machine Learning algorithms.

Data Scientist 52

Data Scientist Data Science Apache Hadoop Machine Learning 52

Pickl AI

MAY 31, 2023

After that, move towards unsupervised learning methods like clustering and dimensionality reduction. It includes regression, classification, clustering, decision trees, and more. Begin by employing algorithms for supervised learning such as linear regression , logistic regression, decision trees, and support vector machines.

Data Science 52

Data Science Python Data Scientist Machine Learning 52

ODSC - Open Data Science

JANUARY 7, 2025

Hadoop, though less common in new projects, is still crucial for batch processing and distributed storage in large-scale environments. Luckily, nothing too complicated is needed, as Tableau is user-friendly while matplotlib is the popular Python library for data visualization.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

phData

FEBRUARY 5, 2024

Setting up the Information Architecture Setting up an information architecture during migration to Snowflake poses challenges due to the need to align existing data structures, types, and sources with Snowflake’s multi-cluster, multi-tier architecture. Get to know all the ins and outs of your upcoming migration. We have you covered !

SQL 52

SQL Database Data Quality Data Warehouse 52