Remove solutions jupyter
article thumbnail

Why Best-of-Breed is a Better Choice than All-in-One Platforms for Data Science

O'Reilly on Data

Do you buy a solution from a big integration company like IBM, Cloudera, or Amazon? Integrated all-in-one platforms assemble many tools together, and can therefore provide a full solution to common workflows. However some assembly is required because they need to be used alongside other products to create full solutions.

article thumbnail

Expand data access through Apache Iceberg using Delta Lake UniForm on AWS

AWS Big Data

Delta Lake UniForm can be a solution to meet this requirement. After creating the Studio Workspace is complete, you are redirected to Jupyter Notebook. Upload Jupyter Notebook Complete the following steps to configure a Jupyter Notebook to use Delta Lake UniForm with Amazon EMR. Download delta-lake-uniform-on-aws.ipynb.

Metadata 122
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Enriching metadata for accurate text-to-SQL generation for Amazon Athena

AWS Big Data

Solution overview This post demonstrates text-to-SQL generation for Athena using an example implemented using Amazon Bedrock. The solution architecture and workflow. The relevant CloudFormation template, Jupyter Notebooks, and details of launching the necessary AWS services are covered in this section.

Metadata 105
article thumbnail

MLOps and DevOps: Why Data Makes It Different

O'Reilly on Data

There is a decades-long tradition of data-centric programming : developers who have been using data-centric IDEs, such as RStudio, Matlab, Jupyter Notebooks, or even Excel to model complex real-world phenomena, should find this paradigm familiar. To plug this gap, frameworks like Metaflow or MLFlow provide a custom solution for versioning.

IT 364
article thumbnail

Accelerate your data workflows with Amazon Redshift Data API persistent sessions

AWS Big Data

aws redshift-data execute-statement --sql "select count(*) from dev.stage_stores" --session-id 5a254dc6-4fc2-4203-87a8-551155432ee4 --session-keep-alive-seconds 10 Solution walkthrough You will use AWS Step Functions to call the Data API because this is one of the more straightforward ways to create a codeless ETL.

article thumbnail

How CFM built a well-governed and scalable data-engineering platform using Amazon EMR for financial features generation

AWS Big Data

In recent years, driven by the commoditization of data storage and processing solutions, the industry has seen a growing number of systematic investment management firms switch to alternative data sources to drive their investment decisions. The bulk of our data scientists are heavy users of Jupyter Notebook.

article thumbnail

The state of data quality in 2020

O'Reilly on Data

Data quality solutions almost always boil down to two big issues: politics and cost. Another one-fifth use a notebook environment (such as Jupyter ). The problem (and partial solution) is that they need quality data to power their AI projects. The remaining 50% (i.e., This includes deciding what is not worth addressing.