Striim

APRIL 3, 2024

This explosion in cloud application use has led to significant challenges in data integration and the delivery of insightful data to stakeholders. With its no-code, zero-maintenance approach, it offers a cost-effective solution for businesses seeking real-time data insights and monitoring. Enterprises in the U.S.

Google Cloud 52

Google Cloud Transportation Data Integration Aggregated Data 52

Pinterest Engineering

SEPTEMBER 5, 2023

We rely on an extensive suite of AI powered products to connect over 460M users to hundreds of billions of Pins, resulting in hundreds of millions of ML inferences per second, hundreds of thousands of ML training jobs per month by just a couple of hundreds of ML engineers.

Engineering 92

Engineering Deep Learning Architecture Project 92

Knowledge Hut

MARCH 27, 2024

A global data explosion is generating almost 2.5 A company can make the right decision by organizing a massive amount of raw data with the right data analytic tool and a professional data analyst. This article will discuss some best big data tools, big data reporting tools and modern data analytic tools in big data.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

Scott Logic

SEPTEMBER 22, 2023

This is the final day of my journal, where day one was all OSPOs, SBOM security, and AI and day two was surveys, statistics and the fragility of the node ecosystem. On the final day there was yet more AI and the looming shadow of the EU Cyber Resilience Act (CRA). If you’re interested in the details, then read on!

PostgreSQL 52

PostgreSQL AWS Education Relational Database 52

Engineering at Meta

MARCH 18, 2024

In this post, we present the design behind Logarithm, and show how it powers AI training debugging use cases. AI training debugging with Logarithm Before looking at Logarithm’s internals, we present support for training systems and model issue debugging, one of the prominent use cases of Logarithm at Meta.

Engineering 91

Engineering Metadata Architecture Designing 91

Snowflake

MARCH 21, 2023

In Snowflake’s 6 Data Science Trends in 2023 , one of the more prominent trends we identified was the emerging use of unified tools and infrastructure for SQL and Python. Data scientists and data engineers often need to stitch multiple tools together to finish a single analysis when using multiple languages.

SQL 52

SQL Python Programming Language Scala 52

ProjectPro

OCTOBER 27, 2021

This blog presents the topmost useful machine learning applications in finance to help you understand how financial markets thrive by adopting AI and ML solutions. There is a wide range of open-source machine learning algorithms and tools that fit exceptionally with financial data. 5Point currently earns an extra $1.5

Finance 52

Finance Machine Learning Project Banking 52

Databand.ai

DECEMBER 29, 2022

He has built everything from feature stores, experimentation platforms, metrics layers, and streaming platforms to analytics tools, data discovery systems, and workflow development platforms, and he believes that applying product thinking to holistic data challenges is the only way to make trustworthy decisions at scale.

BI 52

BI Consulting Data Science Data Governance 52

Cloudera

JANUARY 25, 2022

The explosion of new and more accessible ML tooling means there’s never been a better time to take the leap into predictive analytics than right now. . Embed AI into your applications. We color code the model results and actual cancellation to make the visual comparison. Figure: Launch screen of the Flight Prediction AMP.

Datasets 90

Datasets Machine Learning Accessible Accessibility 90

Towards Data Science

NOVEMBER 4, 2023

Platform Specific Tools and Advanced Techniques Photo by Christopher Burns on Unsplash The modern data ecosystem keeps evolving and new data tools emerge now and then. Image by author It also might be a datalake in the center and it depends on the type of our data platform and tools we use.

Data Engineering 86

Data Engineering Data Engineer Engineering BI 86

Snowflake

SEPTEMBER 18, 2023

With the explosion of AI/ML, users want to be able to interact with their data and ML models. Historically that would involve working with a tooling team or trying to fit something into a presentation. The product owners work with tooling teams, which are often understaffed and have backlog requests that run into months.

Python 118

Python Building Cloud Amazon Web Services 118

U-Next

SEPTEMBER 29, 2022

Collecting and analyzing data can be overwhelming without the proper data sets, analytics tools, and data specialists to help. . Data sharing should be enabled between departments with the right infrastructure and tools. New ideas can be backed up by solid evidence due to the explosion of data in corporations. Low-Quality Data.

Management 52

Management Unstructured Data Data Government 52