ODSC - Open Data Science

JANUARY 7, 2025

Heres what we noticed from analyzing this data, highlighting whats remained the same over the years, and what additions help make the modern data scientist in2025. Data Science Of course, a data scientist should know data science! Joking aside, this does infer particular skills.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

O'Reilly Media

SEPTEMBER 15, 2021

Cloud certifications, specifically in AWS and Microsoft Azure, were most strongly associated with salary increases. As we’ll see later, cloud certifications (specifically in AWS and Microsoft Azure) were the most popular and appeared to have the largest effect on salaries. But we believe that this data shows something significant.

AI 145

AI AI Azure AWS 145

phData

NOVEMBER 8, 2024

Each snapshot has a separate manifest file that keeps track of the data files associated with that snapshot and hence can be restored/queries whenever needed. Versioning also ensures a safer experimentation environment, where data scientists can test new models or hypotheses on historical data snapshots without impacting live data.

Data Lakes 52

Data Lakes Data Warehouse Database Azure 52

Smart Data Collective

NOVEMBER 8, 2020

Data science is an increasingly attractive career path for many people. If you want to become a data scientist, then you should start by looking at the career options available. Northwestern University has a great list of ways that people can pursue a career in data science. Data processing is often done in batches.

Data Engineering 104

Data Engineering Data Engineering Data Engineering Data Engineer 104

Pickl AI

JULY 25, 2023

Unfolding the difference between data engineer, data scientist, and data analyst. Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. Role of Data Scientists Data Scientists are the architects of data analysis.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Precisely

MARCH 9, 2023

As cloud computing platforms make it possible to perform advanced analytics on ever larger and more diverse data sets, new and innovative approaches have emerged for storing, preprocessing, and analyzing information. Hadoop, Snowflake, Databricks and other products have rapidly gained adoption.

Data Lakes 59

Data Lakes Data Warehouse Hadoop Big Data 59

ODSC - Open Data Science

MAY 31, 2023

It is typically a single store of all enterprise data, including raw copies of source system data and transformed data used for tasks such as reporting, visualization, advanced analytics, and machine learning. Data processing happens in batch mode with the data stored at rest and can take minutes or even hours.

Data Lakes 131

Data Lakes Machine Learning Machine Learning Apache Kafka 131

Mlearning.ai

MARCH 15, 2023

Data professionals are in high demand all over the globe due to the rise in big data. The roles of data scientists and data analysts cannot be over-emphasized as they are needed to support decision-making. This article will serve as an ultimate guide to choosing between Data Science and Data Analytics.

Data Science 52

Data Science Analytics Analytics Data Analyst 52

Mlearning.ai

MAY 23, 2023

Answering one of the most common questions I get asked as a Senior Data Scientist — What skills and educational background are necessary to become a data scientist? Photo by Eunice Lituañas on Unsplash To become a data scientist, a combination of technical skills and educational background is typically required.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

JANUARY 13, 2025

The top 10 AI jobs include Machine Learning Engineer, Data Scientist, and AI Research Scientist. Essential skills for these roles encompass programming, machine learning knowledge, data management, and soft skills like communication and problem-solving. Key Skills Experience with cloud platforms (AWS, Azure).

AI 52

AI AI Machine Learning Machine Learning 52

ODSC - Open Data Science

JUNE 7, 2023

Since data is left in its raw form within the data lake, it’s easier for data teams to experiment with models and analysis techniques with greater flexibility. So let’s take a look at a few of the leading industry examples of data lakes. Snowflake Snowflake is a cross-cloud platform that looks to break down data silos.

Data Lakes 52

Data Lakes Azure Data Warehouse Hadoop 52

Pickl AI

NOVEMBER 4, 2024

They are responsible for building and maintaining data architectures, which include databases, data warehouses, and data lakes. Their work ensures that data flows seamlessly through the organisation, making it easier for Data Scientists and Analysts to access and analyse information.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Smart Data Collective

AUGUST 29, 2019

Even very traditional sectors, such as farming, use massive amounts of data to control multiple factors in their business. The Big Data in Agriculture initiative involves over 8,000 researchers , which shows how much demand there is for data scientists in these fields. Online Courses.

Big Data 86

Big Data Big Data Big Data Analytics Big Data Analytics 86

Pickl AI

DECEMBER 4, 2024

The rise of advanced technologies such as Artificial Intelligence (AI), Machine Learning (ML) , and Big Data analytics is reshaping industries and creating new opportunities for Data Scientists. Automated Machine Learning (AutoML) will democratize access to Data Science tools and techniques.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

MARCH 19, 2025

Data Science focuses on analysing data to find patterns and make predictions. Data engineering, on the other hand, builds the foundation that makes this analysis possible. Without well-structured data, Data Scientists cannot perform their work efficiently.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

DagsHub

DECEMBER 11, 2023

DagsHub DagsHub is a centralized Github-based platform that allows Machine Learning and Data Science teams to build, manage and collaborate on their projects. In addition to versioning code, teams can also version data, models, experiments and more. However, these tools have functional gaps for more advanced data workflows.

Machine Learning 98

Machine Learning Machine Learning Data Lakes Data Science 98

Pickl AI

NOVEMBER 28, 2024

Cloud platforms like AWS , Google Cloud Platform (GCP), and Microsoft Azure provide managed services for Machine Learning, offering tools for model training, storage, and inference at scale. Big data tools and Cloud computing platforms have become essential in providing the scalability and processing power required for effective ML workflows.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

APRIL 2, 2024

Building Your Data Science Team Data science talent is in high demand. Here are some options to consider: Hire Data Scientists: This is ideal for complex projects requiring expertise in specific areas. Upskill Existing Employees: Train employees with analytical skills in data science fundamentals.

Data Science 52

Data Science Machine Learning Machine Learning Predictive Analytics 52

The MLOps Blog

JANUARY 23, 2023

When it comes to data complexity, it is for sure that in machine learning, we are dealing with much more complex data. First of all, machine learning engineers and data scientists often use data from different data vendors. Some data sets are being corrected by data entry specialists and manual inspectors.

ML 52

ML ML Data Lakes Machine Learning 52

Heartbeat

JULY 31, 2023

Comet is an all-inclusive cloud-based platform that can help data scientists and machine learning engineers streamline their workflow and improve the efficiency of their experimentation process. Comet also integrates with popular data storage and processing tools like Amazon S3, Google Cloud Storage, and Hadoop.

Machine Learning 52

Machine Learning Machine Learning Deep Learning Deep Learning 52

The MLOps Blog

MAY 31, 2023

So, a better database architecture would be to maintain multiple tables where one of the tables maintains the past 3 months history with session-level details, whereas other tables may contain weekly aggregated click, ATC, and order data. Keeping track of which data was used to run an experiment sometimes becomes painful for a Data Scientist.

ML 59

ML ML Algorithm Machine Learning 59