Pickl AI

DECEMBER 26, 2024

Summary: “Data Science in a Cloud World” highlights how cloud computing transforms Data Science by providing scalable, cost-effective solutions for big data, Machine Learning, and real-time analytics. In Data Science in a Cloud World, we explore how cloud computing has revolutionised Data Science.

Data Science 52

Data Science Cloud Computing Machine Learning Machine Learning 52

Smart Data Collective

JUNE 10, 2022

Are you interested in a career in data science? The Bureau of Labor Statistics reports that there are over 105,000 data scientists in the United States. The average data scientist earns over $108,000 a year. Data Scientist. Data Architect. This is the best time ever to pursue this career track.

Data Science 144

Data Science Data Scientist Machine Learning Machine Learning 144

AWS Machine Learning Blog

OCTOBER 24, 2024

It allows data scientists and machine learning engineers to interact with their data and models and to visualize and share their work with others with just a few clicks. SageMaker Canvas has also integrated with Data Wrangler , which helps with creating data flows and preparing and analyzing your data.

Data Warehouse 110

Data Warehouse Machine Learning Machine Learning Cloud Data 110

Applied Data Science

AUGUST 2, 2021

Automation Automating data pipelines and models ➡️ 6. Team Building the right data science team is complex. With a range of role types available, how do you find the perfect balance of Data Scientists , Data Engineers and Data Analysts to include in your team? Big Ideas What to look out for in 2022 1.

Data Science 130

Data Science Data Scientist ML ML 130

The MLOps Blog

MAY 17, 2023

We also discuss different types of ETL pipelines for ML use cases and provide real-world examples of their use to help data engineers choose the right one. What is an ETL data pipeline in ML? Moreover, ETL pipelines play a crucial role in breaking down data silos and establishing a single source of truth.

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ETL Data Pipeline ML ML 59

phData

AUGUST 6, 2024

As today’s world keeps progressing towards data-driven decisions, organizations must have quality data created from efficient and effective data pipelines. For customers in Snowflake, Snowpark is a powerful tool for building these effective and scalable data pipelines.

Data Pipeline 52

Data Pipeline Python Data Engineering Data Engineering 52

Pickl AI

SEPTEMBER 5, 2024

Summary: This blog provides a comprehensive roadmap for aspiring Azure Data Scientists, outlining the essential skills, certifications, and steps to build a successful career in Data Science using Microsoft Azure. This roadmap aims to guide aspiring Azure Data Scientists through the essential steps to build a successful career.

Azure 52

Azure Data Scientist Data Science Machine Learning 52

IBM Data Science in Practice

MARCH 8, 2023

Additionally, imagine being a practitioner, such as a data scientist, data engineer, or machine learning engineer, who will have the daunting task of learning how to use a multitude of different tools. A feature platform should automatically process the data pipelines to calculate that feature. Spark, Flink, etc.)

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Machine Learning Machine Learning ML ML 264

Towards AI

MARCH 21, 2023

Welcome to the mini tour of data engineering where we will discover how a data engineer is different from a data scientist and analyst. Processes like exploring, cleaning, and transforming the data that make the data as efficient as possible. What are ETL and data pipelines?

Data Engineer 98

Data Engineer Data Engineering Data Engineering Data Engineering 98

Smart Data Collective

SEPTEMBER 23, 2020

Type of Data: structured and unstructured from different sources of data Purpose: Cost-efficient big data storage Users: Engineers and scientists Tasks: storing data as well as big data analytics, such as real-time analytics and deep learning Sizes: Store data which might be utilized.

Data Lakes 135

Data Lakes Data Warehouse Big Data Big Data 135

ODSC - Open Data Science

FEBRUARY 2, 2023

The role of a data scientist is in demand and 2023 will be no exception. To get a better grip on those changes we reviewed over 25,000 data scientist job descriptions from that past year to find out what employers are looking for in 2023. Data Science Of course, a data scientist should know data science!

Data Science 98

Data Science Data Scientist Computer Science Computer Science 98

Data Science Dojo

APRIL 16, 2024

Big data engineer Potential pay range – US$206,000 to 296,000/yr They operate at the backend to build and maintain complex systems that store and process the vast amounts of data that fuel AI applications. With the growing amount of data for businesses, the demand for big data engineers is only bound to grow in 2024.

AI 195

AI AI Machine Learning Machine Learning 195

Smart Data Collective

APRIL 2, 2019

Data Lakes are among the most complex and sophisticated data storage and processing facilities we have available to us today as human beings. Analytics Magazine notes that data lakes are among the most useful tools that an enterprise may have at its disposal when aiming to compete with competitors via innovation.

Data Lakes 106

Data Lakes Big Data Big Data Data Scientist 106

Flipboard

NOVEMBER 24, 2023

In an increasingly digital and rapidly changing world, BMW Group’s business and product development strategies rely heavily on data-driven decision-making. With that, the need for data scientists and machine learning (ML) engineers has grown significantly. A data scientist team orders a new JuMa workspace in BMW’s Catalog.

ML 153

ML ML AWS AI 153

IBM Journey to AI blog

FEBRUARY 26, 2024

Increased data pipeline observability As discussed above, there are countless threats to your organization’s bottom line. That’s why data pipeline observability is so important. MANTA customers have used data lineage to complete their migration projects 40% faster with 30% fewer resources.

Data Pipeline 112

Data Pipeline Data Engineering Data Engineering Data Engineer 112

Smart Data Collective

JUNE 20, 2022

When data leaders move to the cloud, it’s easy to get caught up in the features and capabilities of various cloud services without thinking about the day-to-day workflow of data scientists and data engineers. Failing to make production data accessible in the cloud.

Data Engineering 145

Data Engineering Data Engineering Data Engineer Data Engineering 145

Precisely

FEBRUARY 20, 2025

If you cant use predictive analytics and make quick, confident data-driven decisions, you risk falling behind to your competitors that can. Solution: Ensure real-time insights and predictive analytics are both accurate and actionable with data integration.

Data Silos 69

Data Silos AI AI Data Quality 69

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! Kafka remains the go-to for real-time analytics and streaming.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

The MLOps Blog

JUNE 27, 2023

Some popular end-to-end MLOps platforms in 2023 Amazon SageMaker Amazon SageMaker provides a unified interface for data preprocessing, model training, and experimentation, allowing data scientists to collaborate and share code easily. A self-service infrastructure portal for infrastructure and governance.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

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 Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Data Science Dojo

JULY 3, 2024

Data Engineering : Building and maintaining data pipelines, ETL (Extract, Transform, Load) processes, and data warehousing. Networking Opportunities The popularity of bootcamps has attracted a diverse audience, including aspiring data scientists and professionals transitioning into data science roles.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

ODSC - Open Data Science

FEBRUARY 24, 2023

There are many well-known libraries and platforms for data analysis such as Pandas and Tableau, in addition to analytical databases like ClickHouse, MariaDB, Apache Druid, Apache Pinot, Google BigQuery, Amazon RedShift, etc. Features include an intuitive interface for visualizing datasets and building interactive dashboards.

Exploratory Data Analysis 126

Exploratory Data Analysis Data Visualization Data Analysis Data Analysis 126

AWS Machine Learning Blog

FEBRUARY 5, 2025

The following diagram illustrates the data pipeline for indexing and query in the foundational search architecture. OpenSearch is a powerful, open-source suite that provides scalable and flexible tools for search, analytics, security monitoring, and observabilityall under the Apache 2.0

K-nearest Neighbors 78

K-nearest Neighbors Machine Learning Machine Learning Database 78

IBM Journey to AI blog

AUGUST 12, 2024

It helps companies streamline and automate the end-to-end ML lifecycle, which includes data collection, model creation (built on data sources from the software development lifecycle), model deployment, model orchestration, health monitoring and data governance processes.

Big Data 106

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IBM Journey to AI blog

OCTOBER 12, 2023

Whether building a model from the ground up or fine-tuning a foundation model , data scientists must utilize the necessary training data regardless of that data’s location across a hybrid infrastructure.

AI 93

AI AI Data Scientist Data Governance 93

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 Visualization 52

Data Visualization Analytics Analytics Big Data Analytics 52

Ocean Protocol

NOVEMBER 28, 2024

Introduction The Formula 1 Prediction Challenge: 2024 Mexican Grand Prix brought together data scientists to tackle one of the most dynamic aspects of racing — pit stop strategies. This competition emphasized leveraging analytics in one of the world’s fastest and most data-intensive sports.

Cross Validation 85

Cross Validation Decision Trees Data Scientist Data Science 85

Smart Data Collective

OCTOBER 17, 2022

While growing data enables companies to set baselines, benchmarks, and targets to keep moving ahead, it poses a question as to what actually causes it and what it means to your organization’s engineering team efficiency. What’s causing the data explosion? Big data analytics from 2022 show a dramatic surge in information consumption.

Big Data 119

Big Data Big Data Data Engineering Data Engineering 119

AWS Machine Learning Blog

MARCH 1, 2023

This post is co-written with Suhyoung Kim, General Manager at KakaoGames Data Analytics Lab. To solve this problem, we had to design a strong data pipeline to create the ML features from the raw data and MLOps. Kakao Games is a top video game publisher and developer headquartered in South Korea.

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ODSC - Open Data Science

OCTOBER 18, 2024

Consider these best practices when building the project charter: Collaborate with business leaders Rather than operate in isolation, interview executive sponsors and front-line decision-makers to identify pain points and the biggest opportunities for analytical solutions. However, knowledge transfer to internal teams can pose challenges.

Data Science 52

Data Science Data Scientist Analytics Analytics 52

DataRobot Blog

APRIL 1, 2018

Paxata was a Silver Sponsor at the recent Gartner Data and Analytics Summit in Grapevine Texas. Although some product solutions disrupted the operational reporting market, they require users to know the questions they need to ask their data. 2) Line of business is taking a more active role in data projects.

Analytics 40

Analytics Analytics Data Preparation Augmented Analytics 40

Flipboard

AUGUST 17, 2023

AWS Glue is a serverless data integration service that makes it easy to discover, prepare, and combine data for analytics, ML, and application development. Above all, this solution offers you a native Spark way to implement an end-to-end data pipeline from Amazon Redshift to SageMaker.

ML 123

ML ML AWS Data Warehouse 123

Alation

JUNE 21, 2022

The audience grew to include data scientists (who were even more scarce and expensive) and their supporting resources (e.g., After that came data governance , privacy, and compliance staff. Power business users and other non-purely-analytic data citizens came after that. data pipelines) to support.

DataOps 52

DataOps Data Scientist Data Quality Data Pipeline 52

ODSC - Open Data Science

JANUARY 30, 2024

Not only does it involve the process of collecting, storing, and processing data so that it can be used for analysis and decision-making, but these professionals are responsible for building and maintaining the infrastructure that makes this possible; and so much more. Think of data engineers as the architects of the data ecosystem.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Pickl AI

NOVEMBER 4, 2024

Data Engineering is designing, constructing, and managing systems that enable data collection, storage, and analysis. It involves developing data pipelines that efficiently transport data from various sources to storage solutions and analytical tools. ETL is vital for ensuring data quality and integrity.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Alation

SEPTEMBER 28, 2022

The term has been used a lot more of late, especially in the data analytics industry, as we’ve seen it expand over the past few years to keep pace with new regulations, like the GDPR and CCPA. However, some may confuse it as DevOps for data , but that’s not the case, as there are key differences between DevOps and DataOps.

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DataOps Data Pipeline Data Quality Analytics 52

ODSC - Open Data Science

OCTOBER 15, 2023

Institute of Analytics The Institute of Analytics is a non-profit organization that provides data science and analytics courses, workshops, certifications, research, and development. The courses and workshops cover a wide range of topics, from basic data science concepts to advanced machine learning techniques.

Machine Learning 52

Machine Learning Machine Learning Data Pipeline AI 52