Pickl AI

DECEMBER 25, 2024

With data science and analytics reshaping industries, understanding the distinction between Business Analytics and Data Science is crucial for anyone navigating a career in this field. According to the US Bureau of Labor Statistics, jobs requiring data science skills will grow by 27.9% Masters or Ph.D.

Data Science 52

Data Science Analytics Analytics Data Scientist 52

Pickl AI

SEPTEMBER 19, 2024

Summary: This article compares Spark vs Hadoop, highlighting Spark’s fast, in-memory processing and Hadoop’s disk-based, batch processing model. It discusses performance, use cases, and cost, helping you choose the best framework for your big data needs. What is Apache Hadoop?

Hadoop 52

Hadoop Big Data Big Data Clustering 52

Precisely

MARCH 9, 2023

Data warehouse vs. data lake, each has their own unique advantages and disadvantages; it’s helpful to understand their similarities and differences. In this article, we’ll focus on a data lake vs. data warehouse. It is often used as a foundation for enterprise data lakes.

Data Warehouse 59

Data Warehouse Data Lakes Hadoop Big Data 59

Pickl AI

NOVEMBER 4, 2024

As organisations increasingly rely on data to drive decision-making, understanding the fundamentals of Data Engineering becomes essential. The global Big Data and Data Engineering Services market, valued at USD 51,761.6 Its ability to handle vast amounts of data makes it a cornerstone in big data environments.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

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 Engineering Data Engineering Data Engineer 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. A lot of you who are already in the data science field must be familiar with BigQuery and its advantages.

SQL 52

SQL Database Apache Hadoop Data Science 52

Pickl AI

JULY 20, 2023

Text Analytics and Natural Language Processing (NLP) Projects: These projects involve analyzing unstructured text data, such as customer reviews, social media posts, emails, and news articles. NLP techniques help extract insights, sentiment analysis, and topic modeling from text data.

Analytics 40

Analytics Analytics Big Data Big Data 40

Pickl AI

JULY 18, 2023

Programming for Data Science enables Data Scientists to analyze vast amounts of data and extract meaningful information. There are different programming languages and in this article, we will explore 8 programming languages that play a crucial role in the realm of Data Science.

Data Science 52

Data Science SQL Data Scientist Python 52

Mlearning.ai

MAY 16, 2023

Data engineering is a rapidly growing field that designs and develops systems that process and manage large amounts of data. There are various architectural design patterns in data engineering that are used to solve different data-related problems.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Mlearning.ai

AUGUST 18, 2023

As a discipline that includes various technologies and techniques, data science can contribute to the development of new medications, prevention of diseases, diagnostics, and much more. Utilizing Big Data, the Internet of Things, machine learning, artificial intelligence consulting , etc.,

Data Science 52

Data Science Data Scientist Internet of Things Apache Hadoop 52

DagsHub

OCTOBER 23, 2024

Managing unstructured data is essential for the success of machine learning (ML) projects. Without structure, data is difficult to analyze and extracting meaningful insights and patterns is challenging. This article will discuss managing unstructured data for AI and ML projects. How to properly manage unstructured data.

Machine Learning 52

Machine Learning Machine Learning AI Data Lakes 52

Pickl AI

JANUARY 12, 2025

Summary: The article explores the differences between data driven and AI driven practices. Data-driven and AI-driven approaches have become key in how businesses address challenges, seize opportunities, and shape their strategic directions. Unify Data Sources Collect data from multiple systems into one cohesive dataset.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence AI AI 52