Pickl AI

DECEMBER 25, 2024

Business Analytics requires business acumen; Data Science demands technical expertise in coding and ML. Descriptive analytics is a fundamental method that summarizes past data using tools like Excel or SQL to generate reports. Big data platforms such as Apache Hadoop and Spark help handle massive datasets efficiently.

Data Science 52

Data Science Analytics Analytics Data Scientist 52

Mlearning.ai

MAY 23, 2023

Familiarity with libraries like pandas, NumPy, and SQL for data handling is important. Check out this course to upskill on Apache Spark —  [link] Cloud Computing technologies such as AWS, GCP, Azure will also be a plus. This includes skills in data cleaning, preprocessing, transformation, and exploratory data analysis (EDA).

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Mlearning.ai

JULY 10, 2023

In my 7 years of Data Science journey, I’ve been exposed to a number of different databases including but not limited to Oracle Database, MS SQL, MySQL, EDW, and Apache Hadoop. Views Views in GCP BigQuery are virtual tables defined by SQL query that can display the results of a query or be used as the base for other queries.

SQL 52

SQL Database Apache Hadoop Data Science 52

DagsHub

OCTOBER 23, 2024

Managing unstructured data is essential for the success of machine learning (ML) projects. This article will discuss managing unstructured data for AI and ML projects. You will learn the following: Why unstructured data management is necessary for AI and ML projects. How to properly manage unstructured data.

Machine Learning 52

Machine Learning Machine Learning AI AI 52

IBM Journey to AI blog

JANUARY 18, 2023

They defined it as : “ A data lakehouse is a new, open data management architecture that combines the flexibility, cost-efficiency, and scale of data lakes with the data management and ACID transactions of data warehouses, enabling business intelligence (BI) and machine learning (ML) on all data. ”.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52

Pickl AI

MAY 31, 2023

You should be skilled in using a variety of tools including SQL and Python libraries like Pandas. Proficiency in ML is understood when these are not just present in the aspirant in conceptual ways but also in terms of its applications in solving business problems. It is critical for knowing how to work with huge data sets efficiently.

Data Science 52

Data Science Python Data Scientist Machine Learning 52

Pickl AI

FEBRUARY 23, 2025

Best Big Data Tools Popular tools such as Apache Hadoop, Apache Spark, Apache Kafka, and Apache Storm enable businesses to store, process, and analyse data efficiently. Key Features : Speed : Spark processes data in-memory, making it up to 100 times faster than Hadoop MapReduce in certain applications.

Big Data 52

Big Data Big Data Apache Hadoop Apache Kafka 52