ODSC - Open Data Science

SEPTEMBER 27, 2023

In the ever-evolving world of big data, managing vast amounts of information efficiently has become a critical challenge for businesses across the globe. Unlike traditional data warehouses or relational databases, data lakes accept data from a variety of sources, without the need for prior data transformation or schema definition.

Big Data 98

Big Data Metadata ETL Business Intelligence 98

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 Science 52

Data Science Data Scientist ETL Machine Learning 52

Marktechpost

JUNE 5, 2024

You may use OpenRefine for more than just data cleaning; it can also help you find mistakes and outliers that could compromise your data’s quality. Apache Griffin Apache Griffin is an open-source data quality tool that aims to enhance big data processes.

Data Quality 111

Data Quality Metadata Data Integration ETL 111

ODSC - Open Data Science

OCTOBER 18, 2024

The advent of big data, affordable computing power, and advanced machine learning algorithms has fueled explosive growth in data science across industries. However, research shows that up to 85% of data science projects fail to move beyond proofs of concept to full-scale deployment.

Data Science 52

Data Science ETL Data Scientist Data Quality 52

Marktechpost

AUGUST 27, 2024

This article lists the top data analysis courses that can help you build the essential skills needed to excel in this rapidly growing field. Introduction to Data Analytics This course provides a comprehensive introduction to data analysis, covering the roles of data professionals, data ecosystems, and Big Data tools like Hadoop and Spark.

Data Analysis 57

Data Analysis Python ETL Big Data 57

AWS Machine Learning Blog

NOVEMBER 29, 2023

Amazon SageMaker Studio provides a fully managed solution for data scientists to interactively build, train, and deploy machine learning (ML) models. Amazon SageMaker notebook jobs allow data scientists to run their notebooks on demand or on a schedule with a few clicks in SageMaker Studio.

Data Drift 102

Data Drift BERT Data Scientist Python 102

Mlearning.ai

MAY 16, 2023

There are various architectural design patterns in data engineering that are used to solve different data-related problems. This article discusses five commonly used architectural design patterns in data engineering and their use cases. Finally, the transformed data is loaded into the target system.

Explainability 52

Explainability ETL Big Data Machine Learning 52

Pickl AI

JULY 6, 2023

Thus, making it easier for analysts and data scientists to leverage their SQL skills for Big Data analysis. It applies the data structure during querying rather than data ingestion. This integration allows users to combine the strengths of different tools and frameworks to solve complex big-data challenges.

Big Data 52

Big Data ETL Data Analysis Metadata 52

TransOrg Analytics

AUGUST 9, 2024

Performance: Query performance can be slower compared to optimized data stores. Business Applications: Big Data Analytics : Supporting advanced analytics, machine learning, and artificial intelligence applications. Data Archival : Storing historical data that might be needed for future analysis.

Machine Learning 52

Machine Learning ETL Big Data Data Analysis 52

Marktechpost

JULY 17, 2023

The company’s H20 Driverless AI streamlines AI development and predictive analytics for professionals and citizen data scientists through open source and customized recipes. The platform makes collaborative data science better for corporate users and simplifies predictive analytics for professional data scientists.

Data Mining 96

Data Mining Machine Learning Data Scientist Artificial Intelligence 96

ODSC - Open Data Science

APRIL 4, 2024

Data Analytics in the Age of AI, When to Use RAG, Examples of Data Visualization with D3 and Vega, and ODSC East Selling Out Soon Data Analytics in the Age of AI Let’s explore the multifaceted ways in which AI is revolutionizing data analytics, making it more accessible, efficient, and insightful than ever before.

Data Science 52

Data Science ETL Big Data Machine Learning 52

AWS Machine Learning Blog

AUGUST 21, 2023

We are happy to announce that SageMaker Data Wrangler now supports using Lake Formation with Amazon EMR to provide this fine-grained data access restriction. In this post, we show how to use Lake Formation as a central data governance capability and Amazon EMR as a big data query engine to enable access for SageMaker Data Wrangler.

Data Scientist 87

Data Scientist Machine Learning ML Big Data 87

ODSC - Open Data Science

APRIL 3, 2023

Data Wrangling: Data Quality, ETL, Databases, Big Data The modern data analyst is expected to be able to source and retrieve their own data for analysis. Competence in data quality, databases, and ETL (Extract, Transform, Load) are essential.

Data Science 52

Data Science Big Data ETL Deep Learning 52

Pickl AI

NOVEMBER 4, 2024

Introduction Data Engineering is the backbone of the data-driven world, transforming raw data into actionable insights. As organisations increasingly rely on data to drive decision-making, understanding the fundamentals of Data Engineering becomes essential. ETL is vital for ensuring data quality and integrity.

Data Quality 52

Data Quality ETL Data Integration Machine Learning 52

ODSC - Open Data Science

SEPTEMBER 29, 2023

But, the amount of data companies must manage is growing at a staggering rate. Research analyst firm Statista forecasts global data creation will hit 180 zettabytes by 2025. In our discussion, we cover the genesis of the HPCC Systems data lake platform and what makes it different from other big data solutions currently available.

Big Data 52

Big Data ETL Data Science Data Ingestion 52

Pickl AI

NOVEMBER 15, 2023

Unlike traditional databases, Data Lakes enable storage without the need for a predefined schema, making them highly flexible. Importance of Data Lakes Data Lakes play a pivotal role in modern data analytics, providing a platform for Data Scientists and analysts to extract valuable insights from diverse data sources.

ETL 52

ETL Business Intelligence Metadata Data Analysis 52

Pickl AI

APRIL 6, 2023

Data Engineering is one of the most productive job roles today because it imbibes both the skills required for software engineering and programming and advanced analytics needed by Data Scientists. How to Become an Azure Data Engineer? Which service would you use to create Data Warehouse in Azure?

ETL 52

ETL Big Data Data Ingestion Software Engineer 52

Artificial Corner

JUNE 6, 2023

Timeline of data engineering — Created by the author using canva In this post, I will cover everything from the early days of data storage and relational databases to the emergence of big data, NoSQL databases, and distributed computing frameworks. MongoDB, developed by MongoDB Inc.,

Data Mining 52

Data Mining Big Data ETL Machine Learning 52

ODSC - Open Data Science

OCTOBER 9, 2024

Confirmed sessions related to software engineering include: Building Data Contracts with Open-Source Tools Chronon — Open Source Data Platform for AI/ML Creating APIs That Data Scientists Will Love with FastAPI, SQLAlchemy, and Pydantic Using APIs in Data Science Without Breaking Anything Don’t Go Over the Deep End: Building an Effective OSS Management (..)

Software Engineer 40

Software Engineer Software Development DevOps Machine Learning 40

Mlearning.ai

JULY 10, 2023

And since the advent of cloud data warehouse, I was lucky enough to get a good amount of exposure on Google Cloud Platform in the early stages of the era which became my competitive edge in this wild job market. A lot of you who are already in the data science field must be familiar with BigQuery and its advantages.

Data Science 52

Data Science Big Data ETL Automation 52

Pickl AI

APRIL 26, 2024

Data Warehousing and ETL Processes What is a data warehouse, and why is it important? A data warehouse is a centralised repository that consolidates data from various sources for reporting and analysis. It is essential to provide a unified data view and enable business intelligence and analytics.

Data Analysis 52

Data Analysis Machine Learning ETL Explainability 52

AWS Machine Learning Blog

SEPTEMBER 6, 2024

By following these guidelines, data scientists can quantify the user experience delivered by their generative AI pipelines and communicate meaning to business stakeholders, facilitating ready comparisons across different architectures, such as Retrieval Augmented Generation (RAG) pipelines, off-the-shelf or fine-tuned LLMs, or agentic solutions.

Generative AI 90

Generative AI LLM AI AI 90

Flipboard

DECEMBER 4, 2024

It often requires multiple teams working together and integrating various data sources, tools, and services. For example, creating a targeted marketing app involves data engineers, data scientists, and business analysts using different systems and tools.

ETL 139

ETL Business Intelligence Big Data Architect Machine Learning 139

AWS Machine Learning Blog

SEPTEMBER 18, 2024

An example direct acyclic graph (DAG) might automate data ingestion, processing, model training, and deployment tasks, ensuring that each step is run in the correct order and at the right time. Though it’s worth mentioning that Airflow isn’t used at runtime as is usual for extract, transform, and load (ETL) tasks.

Machine Learning 112

Machine Learning Data Scientist Data Ingestion ML 112

AWS Machine Learning Blog

AUGUST 2, 2024

This is a guest post co-written with Vicente Cruz Mínguez, Head of Data and Advanced Analytics at Cepsa Química, and Marcos Fernández Díaz, Senior Data Scientist at Keepler. About the authors Vicente Cruz Mínguez is the Head of Data & Advanced Analytics at Cepsa Química.

Generative AI 109

Generative AI LLM Machine Learning Data Scientist 109

Marktechpost

NOVEMBER 23, 2024

This article lists the top data analysis courses that can help you build the essential skills needed to excel in this rapidly growing field. Introduction to Data Analytics This course provides a comprehensive introduction to data analysis, covering the roles of data professionals, data ecosystems, and Big Data tools like Hadoop and Spark.

Data Analysis 112

Data Analysis Python ETL Big Data 112