phData

NOVEMBER 4, 2024

With all this packaged into a well-governed platform, Snowflake continues to set the standard for data warehousing and beyond. Snowflake supports data sharing and collaboration across organizations without the need for complex data pipelines.

Machine Learning 69

Machine Learning Machine Learning Data Science ML 69

ODSC - Open Data Science

DECEMBER 5, 2023

We had bigger sessions on getting started with machine learning or SQL, up to advanced topics in NLP, and of course, plenty related to large language models and generative AI. You can see our photos from the event here , and be sure to follow our YouTube for virtual highlights from the conference as well.

Data Science 98

Data Science Artificial Intelligence Artificial Intelligence Machine Learning 98

AWS Machine Learning Blog

MARCH 8, 2023

In order to train a model using data stored outside of the three supported storage services, the data first needs to be ingested into one of these services (typically Amazon S3). This requires building a data pipeline (using tools such as Amazon SageMaker Data Wrangler ) to move data into Amazon S3.

ML 135

ML ML AWS Python 135

phData

JULY 4, 2024

Because it runs Snowflake SQL from an easy-to-use, code-first GUI interface, it can take advantage of everything Snowflake offers, even if the feature is brand new. This blog will cover creating customized nodes in Coalesce, what new advanced features can already be used as nodes, and how to create them as part of your data pipeline.

SQL 52

SQL Data Pipeline Data Engineer Data Engineering 52

Applied Data Science

AUGUST 2, 2021

Automation Automating data pipelines and models ➡️ 6. The most common data science languages are Python and R   —  SQL is also a must have skill for acquiring and manipulating data. The Data Engineer Not everyone working on a data science project is a data scientist.

Data Science 130

Data Science Data Scientist ML ML 130

Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody.

SQL 52

SQL ML ML Python 52

Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody.

SQL 52

SQL ML ML Python 52

ODSC - Open Data Science

FEBRUARY 17, 2023

Cloud Computing, APIs, and Data Engineering NLP experts don’t go straight into conducting sentiment analysis on their personal laptops. Data Engineering Platforms Spark is still the leader for data pipelines but other platforms are gaining ground. Knowing some SQL is also essential.

Deep Learning 111

Deep Learning Data Science Deep Learning Natural Language Processing 111

Flipboard

NOVEMBER 24, 2023

This use case highlights how large language models (LLMs) are able to become a translator between human languages (English, Spanish, Arabic, and more) and machine interpretable languages (Python, Java, Scala, SQL, and so on) along with sophisticated internal reasoning.

Database 158

Database AWS ETL SQL 158

Pickl AI

JULY 25, 2023

Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. Data Visualization: Matplotlib, Seaborn, Tableau, etc.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Dataconomy

MAY 16, 2023

With the explosion of big data and advancements in computing power, organizations can now collect, store, and analyze massive amounts of data to gain valuable insights. Machine learning, a subset of artificial intelligence , enables systems to learn and improve from data without being explicitly programmed.

Data Scientist 156

Data Scientist ML ML Machine Learning 156

AWS Machine Learning Blog

SEPTEMBER 18, 2024

The ZMP analyzes billions of structured and unstructured data points to predict consumer intent by using sophisticated artificial intelligence (AI) to personalize experiences at scale. Additionally, Feast promotes feature reuse, so the time spent on data preparation is reduced greatly.

AWS 126

AWS Machine Learning Machine Learning ML 126

ODSC - Open Data Science

FEBRUARY 2, 2023

Computer Science and Computer Engineering Similar to knowing statistics and math, a data scientist should know the fundamentals of computer science as well. While knowing Python, R, and SQL are expected, you’ll need to go beyond that. Big Data As datasets become larger and more complex, knowing how to work with them will be key.

Data Science 98

Data Science Data Scientist Computer Science Computer Science 98

ODSC - Open Data Science

FEBRUARY 24, 2023

Great Expectations provides support for different data backends such as flat file formats, SQL databases, Pandas dataframes and Sparks, and comes with built-in notification and data documentation functionality. VisiData works with CSV files, Excel spreadsheets, SQL databases, and many other data sources.

Exploratory Data Analysis 126

Exploratory Data Analysis Data Visualization Data Analysis Data Analysis 126

AWS Machine Learning Blog

AUGUST 12, 2024

As the scale and complexity of data handled by organizations increase, traditional rules-based approaches to analyzing the data alone are no longer viable. This is achieved by using the pipeline to transfer data from a Splunk index into an S3 bucket, where it will be cataloged.

ML 127

ML ML AWS AI 127

IBM Journey to AI blog

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

Flipboard

MAY 21, 2025

AI applicationsparticularly those built on large language models (LLMs) require frequent iterations to refine prompts, adjust data pipelines, and optimize outputs. It offers cost-effective vector storage in SQL, combining fast searches with relational database features.

AWS 81

AWS AI AI Database 81

ODSC - Open Data Science

AUGUST 23, 2023

That’s a problem when you’re trying to work with that data in pandas because you have to pull the dataset into the memory of your machine, which can be slow, expensive, and lead to fatal out-of-memory issues. Ponder solves this problem by translating your pandas code to SQL that can be understood by your data warehouse.

Data Warehouse 52

Data Warehouse Data Science Database SQL 52

Precisely

AUGUST 15, 2024

Create an AI-driven data and process improvement loop to continuously enhance your business operations. An increasing number of GenAI tools use large language models that automate key data engineering, governance, and master data management tasks.

AI 64

AI AI Data Quality Data Engineer 64

AWS Machine Learning Blog

SEPTEMBER 24, 2024

An optional CloudFormation stack to deploy a data pipeline to enable a conversation analytics dashboard. Choose an option for allowing unredacted logs for the Lambda function in the data pipeline. This allows you to control which IAM principals are allowed to decrypt the data and view it. For testing, choose yes.

AWS 104

AWS AI AI Analytics 104

Pickl AI

OCTOBER 17, 2024

Databases These are structured data collections managed by Database Management Systems (DBMS). Organisations often extract data from relational databases like MySQL, Oracle, or SQL Server to facilitate analysis. It consolidates data into a single source, facilitating accurate reporting and analytics.

ETL 52

ETL Data Warehouse SQL Data Quality 52

phData

JULY 18, 2024

Large manufacturers are starting to use computer vision artificial intelligence (AI) to detect defects cheaper and more efficiently than using human eyes. Detecting product defects can be time-consuming, costly (both for paying people to catch them and if you don’t catch them soon enough), and tedious.

Machine Learning 52

Machine Learning Machine Learning Natural Language Processing Data Engineer 52

Mlearning.ai

JUNE 16, 2023

Generative AI can be used to automate the data modeling process by generating entity-relationship diagrams or other types of data models and assist in UI design process by generating wireframes or high-fidelity mockups. GPT-4 Data Pipelines: Transform JSON to SQL Schema Instantly Blockstream’s public Bitcoin API.

AI 52

AI AI Data Analysis Data Analysis 52

ODSC - Open Data Science

JANUARY 18, 2024

This individual is responsible for building and maintaining the infrastructure that stores and processes data; the kinds of data can be diverse, but most commonly it will be structured and unstructured data. They’ll also work with software engineers to ensure that the data infrastructure is scalable and reliable.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

IBM Journey to AI blog

JULY 17, 2023

Real-time analytics and BI: Combine data from existing sources with new data to unlock new, faster insights without the cost and complexity of duplicating and moving data across different environments. Presto engine: Incorporates the latest performance enhancements to the Presto query engine.

AI 74

AI AI Machine Learning Machine Learning 74

IBM Journey to AI blog

AUGUST 4, 2023

It’s distributed both in the cloud and on-premises, allowing extensive use and movement across clouds, apps and networks, as well as stores of data at rest. An architecture designed for data democratization aims to be flexible, integrated, agile and secure to enable the use of data and artificial intelligence (AI) at scale.

Data Lakes 73

Data Lakes AI AI Data Governance 73

Pickl AI

OCTOBER 17, 2024

Automation Automation plays a pivotal role in streamlining ETL processes, reducing the need for manual intervention, and ensuring consistent data availability. By automating key tasks, organisations can enhance efficiency and accuracy, ultimately improving the quality of their data pipelines.

ETL 52

ETL Data Warehouse Data Quality Data Governance 52

ODSC - Open Data Science

OCTOBER 13, 2024

Open table formats, such as Delta Lake or Apache Iceberg, add a crucial metadata layer over raw data files, allowing us to manage schema, enforce transactions, and even track changes to datasets over time. Lastly, data version control systems, like lakeFS, allow for a Git-like approach to managing data.

Data Lakes 40

Data Lakes Database Data Pipeline SQL 40

ODSC - Open Data Science

SEPTEMBER 29, 2023

Furthermore, we’ve developed data encryption and governance solutions for HPCC Systems to help secure data, ensure it is only accessed by appropriate personnel, and to create audit trails to ensure data security SLAs and regulations are met. It truly is an all-in-one data lake solution. Tell me more about ECL.

Data Lakes 52

Data Lakes Clustering Big Data Big Data 52

ODSC - Open Data Science

APRIL 26, 2023

Though scripted languages such as R and Python are at the top of the list of required skills for a data analyst, Excel is still one of the most important tools to be used. Because they are the most likely to communicate data insights, they’ll also need to know SQL, and visualization tools such as Power BI and Tableau as well.

Data Analyst 52

Data Analyst Machine Learning Machine Learning Power BI 52

Pickl AI

SEPTEMBER 5, 2024

However, a master’s degree or specialised Data Science or Machine Learning courses can give you a competitive edge, offering advanced knowledge and practical experience. Essential Technical Skills Technical proficiency is at the heart of an Azure Data Scientist’s role.

Azure 52

Azure Data Scientist Data Science Machine Learning 52

Alation

JANUARY 17, 2023

A legacy data stack usually refers to the traditional relational database management system (RDBMS), which uses a structured query language (SQL) to store and process data. While an RDBMS can still be used in a modern data stack, it is not as common because it is not as well-suited for managing big data.

Data Warehouse 52

Data Warehouse ETL Tableau Cloud Data 52

ODSC - Open Data Science

DECEMBER 9, 2024

Yet despite these rich capabilities, challenges stillarise The Fragmentation Challenge With so many modular open-source libraries and frameworks now available, effectively stitching together coherent data science application workflows poses a frequent headache for practitioners.

Data Science 40

Data Science Python Machine Learning Machine Learning 40

ODSC - Open Data Science

SEPTEMBER 20, 2023

Register now while tickets are 50% off. Prices go up Friday!

Data Wrangling 52

Data Wrangling Data Science Machine Learning Machine Learning 52

ODSC - Open Data Science

JANUARY 7, 2025

Computer Science and Computer Engineering Similar to knowing statistics and math, a data scientist should know the fundamentals of computer science as well. While knowing Python, R, and SQL is expected, youll need to go beyond that. Employers arent just looking for people who can program.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

phData

JULY 18, 2023

Support for Numerous Data Sources: Fivetran supports over 200 data sources, including popular databases, applications, and cloud platforms like Salesforce, Google Analytics, SQL Server, Snowflake, and many more. Additionally, unsupported data sources can be integrated using Fivetran’s cloud function connectors.

Data Warehouse 52

Data Warehouse Analytics Analytics Cloud Data 52

The MLOps Blog

MARCH 21, 2023

I have worked with customers where R and SQL were the first-class languages of their data science community. You don’t need a bigger boat : The repository curated by Jacopo Tagliabue shows how several (mostly open-source) tools can be effectively combined together to run data pipelines at scale with very small teams.

Machine Learning 69

Machine Learning Machine Learning Data Scientist ML 69