ODSC - Open Data Science

SEPTEMBER 29, 2023

Data management problems can also lead to data silos; disparate collections of databases that don’t communicate with each other, leading to flawed analysis based on incomplete or incorrect datasets. One way to address this is to implement a data lake: a large and complex database of diverse datasets all stored in their original format.

Data Lakes 52

Data Lakes Clustering Big Data Big Data 52

Data Science Dojo

JULY 6, 2023

Apache Spark: Apache Spark is an open-source, unified analytics engine designed for big data processing. It provides high-speed, in-memory data processing capabilities and supports various programming languages like Scala, Java, Python, and R. It can handle both batch and real-time data processing tasks efficiently.

Data Engineering 195

Data Engineering Data Engineer Data Engineering Data Engineering 195

ODSC - Open Data Science

JUNE 1, 2023

Real-Time ML with Spark and SBERT, AI Coding Assistants, Data Lake Vendors, and ODSC East Highlights Getting Up to Speed on Real-Time Machine Learning with Spark and SBERT Learn more about real-time machine learning by using this approach that uses Apache Spark and SBERT. Well, these libraries will give you a solid start.

Data Lakes 52

Data Lakes ML ML Citizen Data Scientist 52

Flipboard

DECEMBER 11, 2024

Many of these applications are complex to build because they require collaboration across teams and the integration of data, tools, and services. Data engineers use data warehouses, data lakes, and analytics tools to load, transform, clean, and aggregate data. Big Data Architect.

SQL 160

SQL AWS Data Lakes AI 160

AWS Machine Learning Blog

SEPTEMBER 27, 2024

SageMaker Studio runs custom Python code to augment the training data and transform the metadata output from SageMaker Ground Truth into a format supported by the computer vision model training job. The model is then trained using a fully managed infrastructure, validated, and published to the Amazon SageMaker Model Registry.

AWS 119

AWS Data Lakes ML ML 119

ODSC - Open Data Science

AUGUST 31, 2023

When choosing a data structure, it may benefit you to see which has all the components of the CAP theorem and which best suits your needs. Drowning in Data? A Data Lake May Be Your Lifesaver Read this Q&A with HPCC Systems on how data lakes let you spend less time managing data and more time analyzing it.

Clustering 98

Clustering Data Lakes Data Science Artificial Intelligence 98

ODSC - Open Data Science

FEBRUARY 15, 2024

The Future of the Single Source of Truth is an Open Data Lake Organizations that strive for high-performance data systems are increasingly turning towards the ELT (Extract, Load, Transform) model using an open data lake.

Data Lakes 52

Data Lakes Data Visualization Machine Learning Machine Learning 52

AWS Machine Learning Blog

JUNE 18, 2024

The solution harnesses the capabilities of generative AI, specifically Large Language Models (LLMs), to address the challenges posed by diverse sensor data and automatically generate Python functions based on various data formats. The solution only invokes the LLM for new device data file type (code has not yet been generated).

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AWS Python AI AI 132

ODSC - Open Data Science

MARCH 21, 2025

PlotlyInteractive Data Visualization Plotly is a leader in interactive data visualization tools, offering open-source graphing libraries in Python, R, JavaScript, and more. Their solutions, including Dash, make it easier for developers and data scientists to build analytical web applications with minimalcoding.

Data Scientist 52

Data Scientist Data Visualization Data Science Data Lakes 52

ODSC - Open Data Science

SEPTEMBER 12, 2023

Although setting up a database to run your analyses may seem like an arduous task, modern open-source time series databases can provide significant benefits to any scientist running time series analysis on a large data set — and with much less effort than you might imagine.

Data Scientist 97

Data Scientist Database Data Lakes Data Science 97

Towards AI

MARCH 28, 2024

This e-book focuses on adapting large language models (LLMs) to specific use cases by leveraging Prompt Engineering, Fine-Tuning, and Retrieval Augmented Generation (RAG), tailored for readers with an intermediate knowledge of Python. He is looking for someone with project ideas and a basic understanding of AI and coding (preferably Python).

AI 97

AI AI Data Lakes Azure 97

phData

SEPTEMBER 20, 2023

Snowpark is the set of libraries and runtimes in Snowflake that securely deploy and process non-SQL code, including Python , Java, and Scala. On the server side, runtimes include Python, Java, and Scala in the warehouse model or Snowpark Container Services (private preview).

SQL 98

SQL Python Data Lakes Machine Learning 98

Data Science 101

NOVEMBER 7, 2019

Azure Synapse Analytics can be seen as a merge of Azure SQL Data Warehouse and Azure Data Lake. Synapse allows one to use SQL to query petabytes of data, both relational and non-relational, with amazing speed. Python support has been available for a while. Azure Synapse. It’s true, I saw it happen this week.

Data Science 106

Data Science Azure SQL Machine Learning 106

ODSC - Open Data Science

FEBRUARY 24, 2023

These tools will help make your initial data exploration process easy. ydata-profiling GitHub | Website The primary goal of ydata-profiling is to provide a one-line Exploratory Data Analysis (EDA) experience in a consistent and fast solution. Output is a fully self-contained HTML application.

Exploratory Data Analysis 126

Exploratory Data Analysis Data Visualization Data Analysis Data Analysis 126

Mlearning.ai

JULY 8, 2023

EL stands for extract and load, and its primary goal is to just move the data from one place to another where the destination is usually a Data Warehouse or a Data Lake. The most fundamental difference between ELT and ETL is that the former first loads the data into the target storage and, then, processes them.

ETL 52

ETL Azure Python Internet of Things 52

ODSC - Open Data Science

FEBRUARY 2, 2023

This doesn’t mean anything too complicated, but could range from basic Excel work to more advanced reporting to be used for data visualization later on. Computer Science and Computer Engineering Similar to knowing statistics and math, a data scientist should know the fundamentals of computer science as well.

Data Science 98

Data Science Data Scientist Computer Science Computer Science 98

Pickl AI

APRIL 21, 2025

Key Takeaways Big Data focuses on collecting, storing, and managing massive datasets. Data Science extracts insights and builds predictive models from processed data. Big Data technologies include Hadoop, Spark, and NoSQL databases. Data Science uses Python, R, and machine learning frameworks.

Big Data 52

Big Data Big Data Data Science Machine Learning 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

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

Alation

OCTOBER 7, 2021

By viewing data spatially, inferences can be made, and the imagination can be sparked. But in a world where so much data has a location, it’s essential to think spatially. From an ancient lake to a data lake: A paleo perspective. I’ve been getting my hands dirty with data for a long time now.

Data Scientist 98

Data Scientist Data Lakes Data Science SQL 98

Dataversity

MARCH 12, 2021

blog series, we experiment with the most interesting blends of data and tools. Whether it’s mixing traditional sources with modern data lakes, open-source devops on the cloud with protected internal legacy tools, SQL with noSQL, web-wisdom-of-the-crowd with in-house handwritten notes, or IoT […]. In the “Will They Blend?”

Data Lakes 52

Data Lakes SQL Database Data Science 52

AWS Machine Learning Blog

FEBRUARY 21, 2025

This setup uses the AWS SDK for Python (Boto3) to interact with AWS services. He specializes in large language models, cloud infrastructure, and scalable data systems, focusing on building intelligent solutions that enhance automation and data accessibility across Amazons operations.

AWS 124

AWS Natural Language Processing Machine Learning Machine Learning 124

Hacker News

JANUARY 26, 2024

This allows data to be read into DuckDB and moved between these systems in a convenient manner. In modern data analysis, data must often be combined from a wide variety of different sources. Data might sit in CSV files on your machine, in Parquet files in a data lake, or in an operational database.

Database 169

Database Data Analysis Data Analysis Data Lakes 169

AWS Machine Learning Blog

NOVEMBER 12, 2024

He is focused on Big Data, Data Lakes, Streaming and batch Analytics services and generative AI technologies. He is actively working on projects in the ML space and has presented at numerous conferences including Strata and GlueCon. Arghya Banerjee is a Sr.

SQL 119

SQL AWS AI AI 119

O'Reilly Media

OCTOBER 19, 2021

Why: Data Makes It Different. If you peek under the hood of an ML-powered application, these days you will often find a repository of Python code. ML use cases rarely dictate the master data management solution, so the ML stack needs to integrate with existing data warehouses. However, not all Python code is equal.

ML 145

ML ML Data Scientist AWS 145

IBM Data Science in Practice

JANUARY 9, 2024

Solution 4: Integrate 3rd party models with MAS This data science solution predicts anomalies in air compressor assets using an external model. Through Watson Studio, we create a Python wrapper function to get results from the deployed models and integrate the model within Watson Machine Learning.

ML 130

ML ML AI AI 130

Flipboard

AUGUST 17, 2023

Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and ML to deliver the best price-performance at any scale. as the image and Glue Python [PySpark and Ray] as the kernel, then choose Select.

ML 123

ML ML AWS Data Warehouse 123

AWS Machine Learning Blog

MAY 30, 2024

Vitech used Python virtual environments to freeze a stable version of the LangChain dependencies and seamlessly move it from development to production environments. Streamlit offers a user-friendly experience to quickly build interactive and easily deployable solutions using the Python library (used widely at Vitech). langsmith==0.0.43

AI 131

AI AI AWS Database 131

ODSC - Open Data Science

JULY 27, 2023

Choosing a Data Lake Format: What to Actually Look For The differences between many data lake products today might not matter as much as you think. When choosing a data lake, here’s something else to consider. When choosing a data lake, here’s something else to consider.

Data Lakes 52

Data Lakes SQL AI AI 52

AWS Machine Learning Blog

JUNE 20, 2024

Our goal was to improve the user experience of an existing application used to explore the counters and insights data. The data is stored in a data lake and retrieved by SQL using Amazon Athena. You can experiment with and evaluate top FMs for your use case and customize them with your data.

SQL 115

SQL Database AWS Machine Learning 115

Flipboard

JUNE 26, 2023

Companies are faced with the daunting task of ingesting all this data, cleansing it, and using it to provide outstanding customer experience. Typically, companies ingest data from multiple sources into their data lake to derive valuable insights from the data. Jupyter notebooks are web-based interactive platforms.

AWS 123

AWS ML ML ETL 123

The MLOps Blog

JANUARY 23, 2023

These tools may have their own versioning system, which can be difficult to integrate with a broader data version control system. For instance, our data lake could contain a variety of relational and non-relational databases, files in different formats, and data stored using different cloud providers. DVC Git LFS neptune.ai

ML 52

ML ML Data Lakes Machine Learning 52

ODSC - Open Data Science

MAY 8, 2023

To get the data, you will need to follow the instructions in the article: Create a Data Solution on Azure Synapse Analytics with Snapshot Serengeti — Part 1 — Microsoft Community Hub, where you will load data into Azure Data Lake via Azure Synapse. Lastly, upload the data from Azure Subscription.

Azure 52

Azure ML ML Data Models 52

IBM Journey to AI blog

JUNE 14, 2023

As a first step, we’re carefully curating an enterprise-ready data set using our data lake tooling to serve as a foundation for our, well, foundation models. fit into a greater data and AI platform, watsonx, alongside two other key pillars watsonx.data and watsonx.governance.

AI 103

AI AI Natural Language Processing Data Lakes 103

The MLOps Blog

JUNE 27, 2023

For example, if your team is proficient in Python and R, you may want an MLOps tool that supports open data formats like Parquet, JSON, CSV, etc., LakeFS LakeFS is an open-source platform that provides data lake versioning and management capabilities. and programmatically via the Kolena Python client.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

IBM Journey to AI blog

SEPTEMBER 19, 2023

To pursue a data science career, you need a deep understanding and expansive knowledge of machine learning and AI. Your skill set should include the ability to write in the programming languages Python, SAS, R and Scala. And you should have experience working with big data platforms such as Hadoop or Apache Spark.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

AWS Machine Learning Blog

FEBRUARY 28, 2024

Third, despite the larger adoption of centralized analytics solutions like data lakes and warehouses, complexity rises with different table names and other metadata that is required to create the SQL for the desired sources. Set up the SDK for Python (Boto3). medium instance with the Python 3 (Data Science) kernel.

SQL 142

SQL AWS Database ML 142