O'Reilly Media - Data

JULY 18, 2018

While models and algorithms garner most of the media coverage, this is a great time to be thinking about building tools in data. In this post I share slides and notes from a keynote I gave at the Strata Data Conference in London at the end of May. Economic value of data.

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O'Reilly Media - Data

MAY 24, 2018

The O’Reilly Data Show Podcast: A special episode to mark the 100th episode. This episode of the Data Show marks our 100th episode. We had a collection of friends who were key members of the data science and big data communities on hand and we decided to record short conversations with them.

Data Engineering 179

Data Engineering Engineering Data Artificial Inteligence 179

Cloudera

JANUARY 9, 2025

A Name That Matches the Moment For years, Clouderas platform has helped the worlds most innovative organizations turn data into action. Thats why were moving from Cloudera Machine Learning to Cloudera AI. But over the years, data teams and data scientists overcame these hurdles and AI became an engine of real-world innovation.

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Artificial Inteligence Machine Learning Enterprise Artificial Intelligence 85

CIO

AUGUST 9, 2022

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines used by data scientists, data-centric applications, and other data consumers. The data engineer role.

Data Engineering 197

Data Engineering Analytics Engineering Data 197

Xebia

FEBRUARY 28, 2025

These days Data Science is not anymore a new domain by any means. The time when Hardvard Business Review posted the Data Scientist to be the “Sexiest Job of the 21st Century” is more than a decade ago [1]. In 2019 alone the Data Scientist job postings on Indeed rose by 256% [2]. Why is that? That is massively useful.

Technical Review 182

Technical Review Weak Development Team Artificial Inteligence Machine Learning 182

CIO

SEPTEMBER 29, 2022

s SVP and chief data & analytics officer, has a crowâ??s s unique about the [chief data officer] role is it sits at the cross-section of data, technology, and analytics,â?? On the role of the Chief Data Officer: Due to the nature of our business, Travelers has always used data analytics to assess and price risk.

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Artificial Inteligence Machine Learning Travel Technical Review 201

CIO

MARCH 13, 2025

Hes seeing the need for professionals who can not only navigate the technology itself, but also manage increasing complexities around its surrounding architectures, data sets, infrastructure, applications, and overall security. There are data scientists, but theyre expensive, he says. So is Indicium, a global data services company.

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Part-Time VPE Weak Development Team Fractional VPE Fractional CTO 205

Xebia

DECEMBER 23, 2024

Modern Pay-As-You-Go Data Platforms: Easy to Start, Challenging to Control It’s Easier Than Ever to Start Getting Insights into Your Data The rapid evolution of data platforms has revolutionized the way businesses interact with their data. The result? Yet, this flexibility comes with risks.

Data 130

Data Storage Culture Resources 130

Xebia

DECEMBER 23, 2024

Modern Pay-As-You-Go Data Platforms: Easy to Start, Challenging to Control It’s Easier Than Ever to Start Getting Insights into Your Data The rapid evolution of data platforms has revolutionized the way businesses interact with their data. The result? Yet, this flexibility comes with risks.

Data 130

Data Storage Culture Resources 130

TechCrunch

NOVEMBER 18, 2021

In the early 2000s, most business-critical software was hosted on privately run data centers. DevOps fueled this shift to the cloud, as it gave decision-makers a sense of control over business-critical applications hosted outside their own data centers.

Enterprise 344

Enterprise Artificial Inteligence Data Engineering Data Center 344

CIO

SEPTEMBER 12, 2022

The chief information and digital officer for the transportation agency moved the stack in his data centers to a best-of-breed multicloud platform approach and has been on a mission to squeeze as much data out of that platform as possible to create the best possible business outcomes. Data engine on wheels’.

Data Engineering 174

Data Engineering Engineering Data Transportation 174

Xebia

MARCH 30, 2025

“The fine art of data engineering lies in maintaining the balance between data availability and system performance.” ” Ted Malaska At Melexis, a global leader in advanced semiconductor solutions, the fusion of artificial intelligence (AI) and machine learning (ML) is driving a manufacturing revolution.

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Testing Artificial Inteligence Comparison Software Review 130

Cloudera

MAY 19, 2021

In the previous blog post in this series, we walked through the steps for leveraging Deep Learning in your Cloudera Machine Learning (CML) projects. RAPIDS on the Cloudera Data Platform comes pre-configured with all the necessary libraries and dependencies to bring the power of RAPIDS to your projects. Data Ingestion.

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CIO

APRIL 22, 2022

What is data science? Data science is a method for gleaning insights from structured and unstructured data using approaches ranging from statistical analysis to machine learning. Data science gives the data collected by an organization a purpose. Data science vs. data analytics.

Data 210

Data Artificial Inteligence Machine Learning Analytics 210

TechCrunch

JULY 12, 2022

Machine learning can provide companies with a competitive advantage by using the data they’re collecting — for example, purchasing patterns — to generate predictions that power revenue-generating products (e.g. At a high level, Tecton automates the process of building features using real-time data sources.

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Artificial Inteligence Machine Learning Marketing Data Engineering 249

Xebia

MARCH 13, 2025

The implementation was a over-engineered custom Feast implementation using unsupported backend data stores. The engineer that implemented it had left the company by the time I joined. This becomes more important when a company scales and runs more machine learning models in production.

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TechCrunch

AUGUST 17, 2021

Unbundling financial data through APIs and driving data-driven insights with value-add products in Africa keeps getting more exciting as major players continue to raise more money for scale. The company is also describing itself as a machine learning-as-a-service platform.

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Fintech Infrastructure Data Artificial Inteligence 267

Altexsoft

JULY 23, 2020

When speaking of machine learning, we typically discuss data preparation or model building. Living in the shadow, this stage, according to the recent study , eats up 25 percent of data scientists time. MLOps lies at the confluence of ML, data engineering, and DevOps. More time for development of new models.

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Artificial Inteligence Machine Learning DevOps Tools 145

CIO

JULY 28, 2022

For the past few years, IT leaders at a US financial services company have been struggling to hire data scientists to harness the increasing flood of incoming data that, if used properly, could improve customer experience and drive new products. It’s exponentially harder when it comes to data scientists.

Data 215

Data Artificial Inteligence Machine Learning Fractional CTO 215

CIO

DECEMBER 10, 2024

As many companies that have already adopted off-the-shelf GenAI models have found, getting these generic LLMs to work for highly specialized workflows requires a great deal of customization and integration of company-specific data. million on inference, grounding, and data integration for just proof-of-concept AI projects.

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Artificial Inteligence Off-The-Shelf Insurance Analytics 174

TechCrunch

FEBRUARY 2, 2022

RudderStack , a platform that focuses on helping businesses build their customer data platforms to improve their analytics and marketing efforts, today announced that it has raised a $56 million Series B round led by Insight Partners, with previous investors Kleiner Perkins and S28 Capital also participating. Image Credits: RudderStack.

Data 204

Data Artificial Inteligence Machine Learning Architecture 204

TechCrunch

JUNE 2, 2021

The core idea behind Iterative is to provide data scientists and data engineers with a platform that closely resembles a modern GitOps-driven development stack. After spending time in academia, Iterative co-founder and CEO Dmitry Petrov joined Microsoft as a data scientist on the Bing team in 2013. ”

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Artificial Inteligence Machine Learning Open Source Data Engineering 249

TechCrunch

OCTOBER 19, 2021

While collaborating with product developers, Dang and Wang saw that while product developers wanted to use AI, they didn’t have the right tools in which to do it without relying on data scientists. “We They didn’t work with machine learning extensively, so we decided to build tools for technical non-experts.

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Artificial Inteligence Machine Learning Tools Technical Review 248

Dzone - DevOps

DECEMBER 31, 2024

MLOps, or Machine Learning Operations, is a set of practices that combine machine learning (ML), data engineering, and DevOps to streamline and automate the end-to-end ML model lifecycle. MLOps is an essential aspect of the current data science workflows.

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Artificial Inteligence Machine Learning Scalability Data Engineering 96

AWS Machine Learning - AI

NOVEMBER 20, 2024

In today’s data-intensive business landscape, organizations face the challenge of extracting valuable insights from diverse data sources scattered across their infrastructure. The solution combines data from an Amazon Aurora MySQL-Compatible Edition database and data stored in an Amazon Simple Storage Service (Amazon S3) bucket.

Data 107

Data AWS Groups Knowledge Base 107

TechCrunch

OCTOBER 7, 2021

Increasingly, conversations about big data, machine learning and artificial intelligence are going hand-in-hand with conversations about privacy and data protection. They could see that the longer-term issue would be a growing need and priority for data privacy. The germination for Gretel.ai

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Artificial Inteligence Engineering Technical Review Data 246

Cloudera

APRIL 9, 2021

This blog series follows the manufacturing and operations data lifecycle stages of an electric car manufacturer – typically experienced in large, data-driven manufacturing companies. The first blog introduced a mock vehicle manufacturing company, The Electric Car Company (ECC) and focused on Data Collection.

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Cloudera

NOVEMBER 17, 2021

It’s no secret that Data Scientists have a difficult job. It feels like a lifetime ago that everyone was talking about data science as the sexiest job of the 21st century. There’s recognition that it’s nearly impossible to find the unicorn data scientist that was the apple of every CEO’s eye in 2012.

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Artificial Inteligence Machine Learning Hotels Data Engineering 124

The Crazy Programmer

NOVEMBER 6, 2021

Data Scientist. Data scientist is the most demanding profession in the IT industry. Currently, the demand for data scientists has increased 344% compared to 2013. hence, if you want to interpret and analyze big data using a fundamental understanding of machine learning and data structure.

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Artificial Inteligence Blockchain Software Review Artificial Intelligence 290

Hacker Earth Developers Blog

JUNE 26, 2019

Data science is one of the most sought after jobs of the 21st century. But how do you hire a data scientist who fits the bill? According to Firstround.com , in a competitive field like data science, strong candidates often receive 3 or more offers, so success rates of hiring are commonly below 50%. Data Science.

Data 200

Data How To Artificial Inteligence Machine Learning 200

CIO

JUNE 7, 2022

What is data analytics? Data analytics is a discipline focused on extracting insights from data. It comprises the processes, tools and techniques of data analysis and management, including the collection, organization, and storage of data. What are the four types of data analytics?

Analytics 203

Analytics Data Analysis Business Analytics 203

CIO

OCTOBER 13, 2023

Data architect role Data architects are senior visionaries who translate business requirements into technology requirements and define data standards and principles, often in support of data or digital transformations. Data architects are frequently part of a data science team and tasked with leading data system projects.

Data 199

Data Data Engineering Database Administration Artificial Inteligence 199

TechCrunch

NOVEMBER 14, 2022

The complexity of streaming data technologies – not just streaming video but any kind of streaming data – has created a headache around dealing with that high speed data processing. Real-time data startup Quix raises a $12.9M Accordingly, companies like Spark, Flink have spring up to address this ksqlDB.

Data 208

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Cloudera

JANUARY 6, 2021

Python is used extensively among Data Engineers and Data Scientists to solve all sorts of problems from ETL/ELT pipelines to building machine learning models. Apache HBase is an effective data storage system for many workflows but accessing this data specifically through Python can be a struggle.

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Artificial Inteligence Machine Learning Data Applications 133

TechCrunch

JANUARY 10, 2023

The need for data observability, or the ability to understand, diagnose and orchestrate data health across various IT tools, continues to grow as organizations adopt more apps and services. Other observability vendors with substantial backing behind them include Manta , Observe , Better Stack , Coralogix and Unravel Data.

Data 241

Data Software Review Technical Review Systems Review 241

CIO

JUNE 14, 2023

Data and big data analytics are the lifeblood of any successful business. Getting the technology right can be challenging but building the right team with the right skills to undertake data initiatives can be even harder — a challenge reflected in the rising demand for big data and analytics skills and certifications.

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Big Data Analytics Data eLearning 190

TechCrunch

MAY 18, 2022

Heartex, a startup that bills itself as an “open source” platform for data labeling, today announced that it landed $25 million in a Series A funding round led by Redpoint Ventures. We agreed that the only viable solution was to have internal teams with domain expertise be responsible for annotating and curating training data.

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