Erik Bernhardsson

APRIL 1, 2021

It's one of the largest startups in NYC (by several metrics, like valuation or headcount) and it has a world class engineering team that makes me insanely proud. But Vishal (the CEO of Better) convinced me to spent a year or two with him, and learn how the sausage is made. 10 years ago, companies didn't have big data teams.

Data Engineering 151

Data Engineering Engineering Blockchain Software Engineering 151

TIBCO - Connected Intelligence

MAY 20, 2020

While data science and ML processes are focused on building models, Model Ops focuses on operationalizing the entire data science pipeline within a business system. In fact, many organizations have a dedicated Model Ops Engineer to facilitate this process. Deploy/Integrate.

Data 72

Data Machine Learning Artificial Inteligence How To 72

Mobilunity

DECEMBER 21, 2022

Let’s look at a few of the top reasons for hiring data scientists: Data needs analyzing. Data must be read and analyzed carefully. This requires a professional understanding of how to read it and make data-driven findings. Data can enhance products and services. ML Model Evaluation and Tuning.

Data 52

Data How To Machine Learning Artificial Inteligence 52

Cloudera

NOVEMBER 16, 2022

There is a clear consensus that data teams should express their goals and results in business value terms and not in technical, tactical descriptions, such as “improving data engineering” and “better master data management.” . Yet if their only purpose is secure data storage, they know the market will leave them behind.

Data 82

Data Insurance Metrics eBook 82

Altexsoft

JUNE 29, 2021

MLEs are usually a part of a data science team which includes data engineers , data architects, data and business analysts, and data scientists. Who does what in a data science team. Machine learning engineers are relatively new to data-driven companies.

Artificial Inteligence 105

Artificial Inteligence Machine Learning Engineering Data Engineering 105

O'Reilly Media - Ideas

JULY 28, 2020

The first step in building an AI solution is identifying the problem you want to solve, which includes defining the metrics that will demonstrate whether you’ve succeeded. It sounds simplistic to state that AI product managers should develop and ship products that improve metrics the business cares about. Agreeing on metrics.

Marketing 145

Marketing Weak Development Team Metrics UI/UX 145

Puppies, Flowers, Rainbows and Kittens

MAY 17, 2021

There were obvious, objective metrics that I could use to measure my work. Those metrics and my job defined me. I have also managed testers, data scientists, data engineers, DevOps, Security, designers, data analysts, program managers, product managers, corporate IT teams, and some other roles I don’t even remember anymore.

Weak Development Team 40

Weak Development Team How To Leadership Metrics 40

Hacker Earth Developers Blog

AUGUST 16, 2022

Even if you are using YouTube and you search for a video data engineer you will most likely see men, mostly white, and a few men of color. Our last event was about over employment and how to navigate that as a black or brown professional. Also, read: How To Build Safe And ‘PROUD’ Workplaces – A Personal Story.

Technical Review 246

Technical Review Recruiting Systems Review Education 246

Cloudera

SEPTEMBER 23, 2021

Actually, that metric has dropped to three seconds since that study was conducted a decade ago. ” This is all about IT systems inside enterprises, which is where the data rubber meets the digital road. How to Manage Fast Data. Slowpokes need not apply.

Data 83

Data Sport Report Sustainability 83

Mentormate

DECEMBER 12, 2023

We also discussed how to tailor AI to predict readmissions, offering a targeted solution that enhances patient care while effectively cutting costs and improving the patient’s well-being. This data then undergoes manual cleaning to address inconsistencies, from measurement outliers to data entry mistakes.

Artificial Inteligence 52

Artificial Inteligence Machine Learning Technical Review Development 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. Built By Experts At The Leading Edge Of ML innovation.

Machine Learning 85

Machine Learning Artificial Inteligence Telecommunications Enterprise 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

The Accidental Successful CIO

MAY 12, 2021

CIOs need to understand how to make use of new business intelligence tools Image Credit: deepak pal. Modern CIOs need to understand that Business intelligence (BI) leverages software and services to transform data into actionable insights that inform an company’s strategic and tactical business decisions.

Business Intelligence 90

Business Intelligence Business Analytics Analytics Off-The-Shelf 90

TechCrunch

JUNE 17, 2021

Now, three alums that worked with data in the world of Big Tech have founded a startup that aims to build a “metrics store” so that the rest of the enterprise world — much of which lacks the resources to build tools like this from scratch — can easily use metrics to figure things out like this, too.

Metrics 247

Metrics Tools Data Big Data 247

Altexsoft

JUNE 25, 2019

If we look at the hierarchy of needs in data science implementations, we’ll see that the next step after gathering your data for analysis is data engineering. This discipline is not to be underestimated, as it enables effective data storing and reliable data flow while taking charge of the infrastructure.

Data Engineering 106

Data Engineering Engineering Data Artificial Inteligence 106

CIO

NOVEMBER 29, 2022

For data warehouses, it can be a wide column analytical table. Many companies reach a point where the rate of complexity exceeds the ability of data engineers and architects to support the data change management speed required for the business. Data and cloud strategy must align.

Organization 279

Organization Technical Review Data Artificial Inteligence 279

O'Reilly Media - Ideas

NOVEMBER 13, 2018

There are also many important considerations that go beyond optimizing a statistical or quantitative metric. What is needed are data scientists who can interrogate the data and understand the underlying distributions, working alongside domain experts who can evaluate models holistically. Real modeling begins once in production.

Machine Learning 90

Machine Learning Artificial Inteligence Software Review Conference 90

O'Reilly Media - Ideas

MARCH 31, 2020

Start with a simple project, build your infrastructure, learn how to use your data effectively, build relationships within the organization, then make the leap. Without large amounts of good raw and labeled training data, solving most AI problems is not possible. How do you select what to work on?

Product Management 137

Product Management Artificial Inteligence Machine Learning Software Review 137

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 81

Fractional CTO Software CTO Sustainability 81

Netflix Tech

MARCH 2, 2021

At Netflix, our data scientists span many areas of technical specialization, including experimentation, causal inference, machine learning, NLP, modeling, and optimization. Together with data analytics and data engineering, we comprise the larger, centralized Data Science and Engineering group.

Machine Learning 83

Machine Learning Artificial Inteligence Culture Analysis 83

Netflix Tech

SEPTEMBER 18, 2020

A role in data science eventually seemed like a natural transition, but it wasn’t without its hurdles: With my consulting background, I had to go through a few other roles first while learning how to code on the side.

Data 89

Data Analytics Culture Video 89

Erik Bernhardsson

OCTOBER 27, 2015

Looking back on my own situation I should have spent a lot more time figuring out how to get other people excited about my ideas instead of perfecting ML algorithms (maybe similar to last question). What do you wish you knew earlier about being a data scientist? How do you respond when you hear the phrase ‘big data’?

Data 100

Data Big Data Machine Learning Artificial Inteligence 100

Erik Bernhardsson

OCTOBER 27, 2015

Looking back on my own situation I should have spent a lot more time figuring out how to get other people excited about my ideas instead of perfecting ML algorithms (maybe similar to last question). What do you wish you knew earlier about being a data scientist? How do you respond when you hear the phrase ‘big data’?

Data 100

Data Big Data Machine Learning Artificial Inteligence 100

Kentik

MAY 16, 2016

Using the Data Explorer API for Added-value Content. Kentik Detect™ is a powerful solution that ingests and stores large volumes of network data on a per device, per customer basis. The data is stored in the Kentik Data Engine™, a timeseries database that unifies flow records (NetFlow v5/9, IPFIX, sFlow) with BGP, Geo-IP, and SNMP.

PHP 40

PHP Metrics Network Data 40

AWS Machine Learning - AI

JANUARY 26, 2024

Many customers are looking for guidance on how to manage security, privacy, and compliance as they develop generative AI applications. We first delve into the vulnerabilities, threats, and risks that arise from the implementation, deployment, and use of LLM solutions, and provide guidance on how to start innovating with security in mind.

Artificial Inteligence 115

Artificial Inteligence Generative AI Security Applications 115

Apiumhub

APRIL 1, 2021

This book will help you become a contributor on a data science team, deploy a structured lifecycle approach to data analytics problems, apply appropriate analytic techniques and tools to analyzing big data, learn how to tell a compelling story with data to drive business action.

Artificial Inteligence 52

Artificial Inteligence Data Handbook Machine Learning 52

O'Reilly Media - Ideas

DECEMBER 6, 2018

We’ve talked about data, models, and compute mainly in the context of traditional performance measures: namely, optimizing machine learning or even business metrics. In a recent survey , we found strong awareness and concern over these issues on the part of data scientists and data engineers.

Technology 76

Technology Artificial Inteligence Machine Learning Hardware 76

O'Reilly Media - Ideas

MAY 1, 2019

60 Minutes to Better Product Metrics , July 10. Data science and data tools. Practical Linux Command Line for Data Engineers and Analysts , May 20. First Steps in Data Analysis , May 20. Systems engineering and operations. Unlock Your Potential , July 9. Business Fundamentals , July 10.

Course 45

Course Training Artificial Inteligence Machine Learning 45

ParkMyCloud

JANUARY 17, 2020

Can demonstrate how to build and deploy applications on AWS. Can deploy and define metrics, monitoring and logging systems on AWS. . Azure Data Engineer Associate. Professional Data Engine er. Intended for individuals that enable data-driven decision making by collecting, transforming, and publishing data.

Google Cloud 9

Google Cloud Azure AWS Cloud 9

Cloudera

MAY 13, 2021

Performance metrics appear in charts and graphs. . We compare the current run of a job to a baseline derived from performance metrics. Fixed Reports / Data Engineering jobs . Fixed Reports / Data Engineering Jobs. Data Engineering jobs only. Data Engineering jobs. Report Format.

Data Engineering 74

Data Engineering Cloud Weak Development Team Resources 74

Kentik

NOVEMBER 16, 2015

KDE handles over 10B flow records/day with a microservice architecture that's optimized using metrics. Here at Kentik, our Kentik Detect service is powered by a multi-tenant big data datastore called Kentik Data Engine. And that leads us to metrics. Health checks and series metrics. The life of a query.

Metrics 40

Metrics Microservices Linux Architecture 40

Altexsoft

JANUARY 26, 2022

In recent years, it’s getting more common to see organizations looking for a mysterious analytics engineer. As you may guess from the name, this role sits somewhere in the middle of a data analyst and data engineer, but it’s really neither one nor the other. Here’s the video explaining how data engineers work.

Analytics 59

Analytics Engineering Data Engineering Software Engineering 59

Cloudera

NOVEMBER 17, 2021

You know the one, the mathematician / statistician / computer scientist / data engineer / industry expert. Some companies are starting to segregate the responsibilities of the unicorn data scientist into multiple roles (data engineer, ML engineer, ML architect, visualization developer, etc.),

Machine Learning 125

Machine Learning Artificial Inteligence Hotels Data Engineering 125

Altexsoft

SEPTEMBER 9, 2022

More importantly, it facilitates the interaction of data consumers with information, i.e., people know which data the company has, where it is (which is especially important in today’s distributed environments), and how to find it – to derive maximum business value from digital assets. Metadata storage.

Tools 59

Tools Technical Review Software Review Systems Review 59

Altexsoft

AUGUST 19, 2022

You can personalize dashboards and interfaces, create custom reports and visualizations, and even set up alerts on specific KPIs to notify your team of important metrics updates. There’s also a vast online knowledge base with descriptions, tips, how-to guides , and best practices. How to start with Power BI? So here we go.

Weak Development Team 52

Weak Development Team Data Azure Analytics 52

AWS Machine Learning - AI

FEBRUARY 19, 2024

In this post, we walk through how to use the Titan Image Generator and Titan Multimodal Embeddings models via the AWS Python SDK. Kai Zhu currently works as Cloud Support Engineer at AWS, helping customers with issues in AI/ML related services like SageMaker, Bedrock, etc. b64encode(image_file.read()).decode("utf8")

Generative AI 91

Generative AI AWS Machine Learning Artificial Inteligence 91

TechCrunch

MAY 7, 2021

The pandemic has just pushed edtech mainstream, but language-learning startup Duolingo had already spent the past decade figuring out how to build a successful edtech app. Amid the IPO gold rush, how should we value fintech startups? How to attract large investors to your direct investing platform. billion by 2026.

Fintech 246

Fintech Windows Healthcare Analytics 246