TechCrunch

AUGUST 8, 2022

. “[Livneh founded Equalum] to bring simplicity to the data integration market and to enable … organizations to make decisions based on real-time data rather than historical and inaccurate data.” ” Image Credits: Equalum. But he emphasized the lucrativeness of the opportunity. billion in 2022. .”

Company 191

Company Data Cloud Google Cloud 191

AWS Machine Learning - AI

MARCH 13, 2025

However, customer interaction data such as call center recordings, chat messages, and emails are highly unstructured and require advanced processing techniques in order to accurately and automatically extract insights. Success metrics The early results have been remarkable.

Generative AI 97

Generative AI CTO Coach AWS Artificial Inteligence 97

Cloudera

OCTOBER 5, 2020

Cloudera Data Platform Powered by NVIDIA RAPIDS Software Aims to Dramatically Increase Performance of the Data Lifecycle Across Public and Private Clouds. This exciting initiative is built on our shared vision to make data-driven decision-making a reality for every business. Compared to previous CPU-based architectures, CDP 7.1

Enterprise 93

Enterprise Cloud Data Machine Learning 93

O'Reilly Media - Ideas

APRIL 2, 2019

About 10 months ago, Databricks announced MLflow , a new open source project for managing machine learning development (full disclosure: Ben Lorica is an advisor to Databricks). We thought that given the lack of clear open source alternatives, MLflow had a decent chance of gaining traction, and this has proven to be the case.

Machine Learning 108

Machine Learning Artificial Inteligence Government Tools 108

Cloudera

MAY 13, 2021

Our Choose the Right Stream Processing Engine for Your Data Needs whitepaper makes those comparisons for you, so you can quickly and confidently determine which engine best meets your key business requirements. When evaluating a stream processing engine, consider its processing abstraction capabilities.

Engineering 102

Engineering Comparison Open Source Scalability 102

O'Reilly Media - Ideas

NOVEMBER 13, 2018

There are also many important considerations that go beyond optimizing a statistical or quantitative metric. Given the growing interest in data privacy among users and regulators, there is a lot of interest in tools that will enable you to build ML models while protecting data privacy. Real modeling begins once in production.

Machine Learning 111

Machine Learning Artificial Inteligence Software Review Conference 111

O'Reilly Media - Data

MARCH 22, 2018

At DataScience.com , where I’m a lead data scientist, we feel passionately about the ability of practitioners to use models to ensure safety, non-discrimination, and transparency. Analysts and data scientists can possibly use model comparison and evaluation methods to assess the accuracy of the models.

Off-The-Shelf 177

Off-The-Shelf Machine Learning Artificial Inteligence Weak Development Team 177

AWS Machine Learning - AI

MARCH 18, 2025

Additionally, the complexity increases due to the presence of synonyms for columns and internal metrics available. This retrieved data is used as context, combined with the original prompt, to create an expanded prompt that is passed to the LLM. In just a few minutes you can build powerful data apps using only Python.

Artificial Inteligence 85

Artificial Inteligence Applications Generative AI Off-The-Shelf 85

d2iq

FEBRUARY 19, 2021

Components that are unique to data engineering and machine learning (red) surround the model, with more common elements (gray) in support of the entire infrastructure on the periphery. Before you can build a model, you need to ingest and verify data, after which you can extract features that power the model.

Artificial Inteligence 103

Artificial Inteligence Machine Learning Technical Review Software Review 103

O'Reilly Media - Ideas

DECEMBER 6, 2018

Progress in research has been made possible by the steady improvement in: (1) data sets, (2) hardware and software tools, and (3) a culture of sharing and openness through conferences and websites like arXiv. Novices and non-experts have also benefited from easy-to-use, open source libraries for machine learning.

Technology 103

Technology Artificial Inteligence Machine Learning Hardware 103

Cloudera

JUNE 26, 2023

Here are some tips and tricks of the trade to prevent well-intended yet inappropriate data engineering and data science activities from cluttering or crashing the cluster. For data engineering and data science teams, CDSW is highly effective as a comprehensive platform that trains, develops, and deploys machine learning models.

Tools 76

Tools Data Engineering Analytics Testing 76

Netflix Tech

NOVEMBER 22, 2019

In this session, we discuss the technologies used to run a global streaming company, growing at scale, billions of metrics, benefits of chaos in production, and how culture affects your velocity and uptime. Technology advancements in content creation and consumption have also increased its data footprint.

AWS 15

AWS Open Source Linux Engineering Management 15

Erik Bernhardsson

OCTOBER 27, 2015

Anyway, reposting the full interview: As part of my interviews with Data Scientists I recently caught up with Erik Bernhardsson who is famous in the world of ‘Big Data’ for his open source contributions, his leading of teams at Spotify, and his various talks at various conferences. How do you know what is good enough?

Data 101

Data Big Data Machine Learning Artificial Inteligence 101

Erik Bernhardsson

OCTOBER 27, 2015

Anyway, reposting the full interview: As part of my interviews with Data Scientists I recently caught up with Erik Bernhardsson who is famous in the world of ‘Big Data’ for his open source contributions, his leading of teams at Spotify, and his various talks at various conferences. How do you know what is good enough?

Data 100

Data Big Data Machine Learning Artificial Inteligence 100

O'Reilly Media - Ideas

JUNE 19, 2019

First, the machine learning community has conducted groundbreaking research in many areas of interest to companies, and much of this research has been conducted out in the open via preprints and conference presentations. Quality depends not just on code, but also on data, tuning, regular updates, and retraining.

Government 103

Government Artificial Inteligence Machine Learning Testing 103

O'Reilly Media - Ideas

MARCH 31, 2020

The prospect of taking on a costly data infrastructure project is daunting. If your company is starting out on this path, it’s important to recognize that there are now widely available open source tools and commercial platforms that can power this foundation for you. How do you select what to work on?

Product Management 145

Product Management Artificial Inteligence Machine Learning Weak Development Team 145

Altexsoft

MAY 27, 2020

But, in any case, the pipeline would provide data engineers with means of managing data for training, orchestrating models, and managing them on production. Monitoring tools are often constructed of data visualization libraries that provide clear visual metrics of performance. Source: retentionscience.com.

Machine Learning 89

Machine Learning Artificial Inteligence Architecture Training 89

CIO

JUNE 14, 2023

Additionally, it is vital to be able to execute computing operations on the 1000+ PB within a multi-parallel processing distributed system, considering that the data remains dynamic, constantly undergoing updates, deletions, movements, and growth. In the case of intelligent operations, real-time data informs immediate operational decisions.

Data 97

Data Scalability Storage Big Data 97

Cloudera

MAY 18, 2021

That is accomplished by delivering most technical use cases through a primarily container-based CDP services (CDP services offer a distinct environment for separate technical use cases e.g., data streaming, data engineering, data warehousing etc.) Quantifiable improvements to Apache open source projects.

Cloud 86

Cloud Technical Review Storage Backup 86

Cloudera

AUGUST 26, 2020

Informatica and Cloudera deliver a proven set of solutions for rapidly curating data into trusted information. Informatica’s comprehensive suite of Data Engineering solutions is designed to run natively on Cloudera Data Platform — taking full advantage of the scalable computing platform.

Data 84

Data Machine Learning Artificial Inteligence Disaster Recovery 84

O'Reilly Media - Ideas

MARCH 1, 2022

It is not open source, and is now entering private beta. The Information Battery : Pre-computing and caching data when energy costs are low to minimize energy use when power costs are high is a good way to save money and take advantage of renewable energy sources. No blockchain required.

Trends 116

Trends Blockchain Serverless Malware 116

Altexsoft

OCTOBER 21, 2022

Similar to Google in web browsing and Photoshop in image processing, it became a gold standard in data streaming, preferred by 70 percent of Fortune 500 companies. Apache Kafka is an open-source, distributed streaming platform for messaging, storing, processing, and integrating large data volumes in real time.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Open Source 93

Invid Group

AUGUST 28, 2024

They can be proprietary, third-party, open-source, and run either on-premises or in the cloud. Make sure to implement external and internal metrics using configuration-driven approaches in the solution. External metrics can be implemented using Business Intelligence (BI) tools and shared with the clients to measure performance.

Technical Review 52

Technical Review Artificial Inteligence Performance Azure 52

Cloudera

FEBRUARY 25, 2021

They need strong data exploration and visualization skills, as well as sufficient data engineering chops to fix the gaps they find in their initial study. Build a scikit-learn model to predict churn using customer telco data, and interpret each prediction with LIME. MLflow for Experiment Tracking.

Machine Learning 84

Machine Learning Artificial Inteligence Enterprise Telecommunications 84

Netflix Tech

MARCH 7, 2024

Berg , Romain Cledat , Kayla Seeley , Shashank Srikanth , Chaoying Wang , Darin Yu Netflix uses data science and machine learning across all facets of the company, powering a wide range of business applications from our internal infrastructure and content demand modeling to media understanding.

System 94

System Machine Learning Artificial Inteligence Open Source 94

Apiumhub

NOVEMBER 20, 2023

With 16 years of professional experience in software engineering, including roles as CTO and CEO, he has become a prominent speaker at Green Software events in Germany. His primary responsibility is to integrate sustainability into the engineering roadmap and utilize the company’s portfolio to champion sustainability solutions.

Fractional CTO 83

Fractional CTO Software CTO Sustainability 83

Altexsoft

FEBRUARY 10, 2021

Similar to how DevOps once reshaped the software development landscape, another evolving methodology, DataOps, is currently changing Big Data analytics — and for the better. DataOps is a relatively new methodology that knits together data engineering, data analytics, and DevOps to deliver high-quality data products as fast as possible.

Analytics 75

Analytics DevOps Development Software Review 75

Altexsoft

MAY 14, 2021

On top of that, new technologies are constantly being developed to store and process Big Data allowing data engineers to discover more efficient ways to integrate and use that data. You may also want to watch our video about data engineering: A short video explaining how data engineering works.

Big Data 78

Big Data Analytics Tools Applications 78

Netflix Tech

NOVEMBER 22, 2019

In this session, we discuss the technologies used to run a global streaming company, growing at scale, billions of metrics, benefits of chaos in production, and how culture affects your velocity and uptime. Technology advancements in content creation and consumption have also increased its data footprint.

AWS 40

AWS Open Source Linux Off-The-Shelf 40

Netflix Tech

NOVEMBER 22, 2019

In this session, we discuss the technologies used to run a global streaming company, growing at scale, billions of metrics, benefits of chaos in production, and how culture affects your velocity and uptime. Technology advancements in content creation and consumption have also increased its data footprint.

AWS 40

AWS Open Source Linux Off-The-Shelf 40

Kentik

OCTOBER 2, 2017

That’s why network operations has for years involved deployment of a mix of different commercial, open-source, and home-grown tools. Another API-based option that we’ve developed for our customers is Kentik Connect Pro, a plug-in that we worked with Grafana to develop for their popular open-source data graphing software.

Open Source 40

Open Source Network Metrics System 40

Netflix Tech

SEPTEMBER 10, 2024

Dynomite is a Netflix open source wrapper around Redis that provides a few additional features like auto-sharding and cross-region replication, and it provided Pushy with low latency and easy record expiry, both of which are critical for Pushy’s workload. As Pushy’s portfolio grew, we experienced some pain points with Dynomite.

Systems Review 93

Systems Review Software Review Technical Review Policies 93

Altexsoft

DECEMBER 15, 2021

The rest is done by data engineers, data scientists , machine learning engineers , and other high-trained (and high-paid) specialists. For better guidance, we’ve divided existing AutoML offerings into three large groups — tech giants, specific end-to-end AutoML platforms, and free open source libraries.

Machine Learning 59

Machine Learning Artificial Inteligence How To Open Source 59

Altexsoft

DECEMBER 23, 2022

Whether your goal is data analytics or machine learning , success relies on what data pipelines you build and how you do it. But even for experienced data engineers, designing a new data pipeline is a unique journey each time. Data engineering in 14 minutes. Source: Qubole. Flexibility.

Tools 52

Tools Software Review Systems Review Testing 52

Mobilunity

OCTOBER 30, 2024

Emmanuel Belo, the Business Unit Manager at Camptocamp, a Swiss company developing and integrating open-source software, points out the ability of the outstaffing company to hire engineers swiftly: “Mobilunity was of great help at the time we needed to scale the team quickly.” Monitoring key metrics. Regular check-ins.

Technical Review 52

Technical Review Software Review Development How To 52

Altexsoft

JULY 18, 2023

Maintained by the Apache Software Foundation, Apache Spark is an open-source, unified engine designed for large-scale data analytics. With its native support for in-memory distributed processing and fault tolerance, Spark empowers users to build complex, multi-stage data pipelines with relative ease and efficiency.

Weak Development Team 52

Weak Development Team Big Data Data Machine Learning 52

Kentik

MAY 31, 2017

Some tools present insights gleaned from the collection of device metrics while others use network flows. Other tools gain insight through analysis of packet data, and so on. In many cases, multiple, separate tools receive the same set of source network data but retain different data subsets. DNS log data.

Network 40

Network Tools Big Data Engineering 40