CIO

FEBRUARY 14, 2023

By George Trujillo, Principal Data Strategist, DataStax Increased operational efficiencies at airports. Investments in artificial intelligence are helping businesses to reduce costs, better serve customers, and gain competitive advantage in rapidly evolving markets. Real-time data involves a continuous flow of data in motion.

Artificial Inteligence 290

Artificial Inteligence Strategy Data Machine Learning 290

The Accidental Successful CIO

JANUARY 25, 2023

CIOs Need To Prepare For The Arrival Of AI CIOs can remember not all that long ago that AI was the exclusive domain of data scientists. All people have to do is to plug data into standardized AI templates. These templates still require tech-savvy users to be used and can take weeks of model training, testing and validation.

Artificial Inteligence 98

Artificial Inteligence Artificial Intelligence Machine Learning Training 98

AWS Machine Learning - AI

JANUARY 26, 2024

Generative artificial intelligence (AI) applications built around large language models (LLMs) have demonstrated the potential to create and accelerate economic value for businesses. We then discuss how building on a secure foundation is essential for generative AI.

Artificial Inteligence 119

Artificial Inteligence Generative AI Security Applications 119

OTS Solutions

MARCH 14, 2019

There Are Top Seven Tips for Scaling Your Artificial Intelligence Strategy. In just the last few years, a large number of enterprises have started to work on incorporating an artificial intelligence strategy into their business. They will learn how to use apps that are enhanced with AI.

Artificial Inteligence 140

Artificial Inteligence Artificial Intelligence Strategy Technical Review 140

Netflix Tech

MARCH 4, 2024

Operational automation–including but not limited to, auto diagnosis, auto remediation, auto configuration, auto tuning, auto scaling, auto debugging, and auto testing–is key to the success of modern data platforms. We have also noted a great potential for further improvement by model tuning (see the section of Rollout in Production).

Machine Learning 84

Machine Learning Artificial Inteligence Data Systems Review 84

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 338

Analytics Data Analysis Business Analytics 338

CIO

JUNE 23, 2023

According to the MIT Technology Review Insights Survey, an enterprise data strategy supports vital business objectives including expanding sales, improving operational efficiency, and reducing time to market. The problem is today, just 13% of organizations excel at delivering on their data strategy.

Strategy 289

Strategy Technical Review Data Software Review 289

Altexsoft

JUNE 29, 2021

In a world fueled by disruptive technologies, no wonder businesses heavily rely on machine learning. For example, Netflix takes advantage of ML algorithms to personalize and recommend movies for clients, saving the tech giant billions. The role of a machine learning engineer in the data science team.

Artificial Inteligence 105

Artificial Inteligence Machine Learning Engineering Data Engineering 105

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.

Machine Learning 98

Machine Learning Artificial Inteligence Data Data Engineering 98

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. e-commerce recommendations). One of its proponents is Mike Del Balso, the CEO of Tecton.

Artificial Inteligence 249

Artificial Inteligence Machine Learning Marketing Data Engineering 249

Cloudera

FEBRUARY 16, 2022

While it is a little dated, one amusing example that has been the source of countless internet memes is the famous, “is this a chihuahua or a muffin?” In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. Machine Learning Model Lineage.

Machine Learning 86

Machine Learning Artificial Inteligence Weak Development Team Construction 86

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

Artificial Inteligence 246

Artificial Inteligence Technical Review Engineering Data 246

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.

Machine Learning 137

Machine Learning Artificial Inteligence Data Marketing 137

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.

Open Source 203

Open Source Weak Development Team Artificial Inteligence Data 203

O'Reilly Media - Data

APRIL 3, 2018

Strata Data London will introduce technologies and techniques; showcase use cases; and highlight the importance of ethics, privacy, and security. The growing role of data and machine learning cuts across domains and industries. Data Science and Machine Learning sessions will cover tools, techniques, and case studies.

Machine Learning 155

Machine Learning Artificial Inteligence Company Case Study 155

Perficient

FEBRUARY 13, 2023

Introduction: We often end up creating a problem while working on data. So, here are few best practices for data engineering using snowflake: 1.Transform Using COPY and SNOWPIPE is the fastest and cheapest way to load data. In fact, this is another example of using the right tools. I’m here.

Data Engineering 69

Data Engineering Engineering Data Storage 69

CIO

AUGUST 4, 2022

For example, a football team consisting of 11 quarterbacks would get crushed in a game against talented linemen, running backs and receivers. Interestingly, many companies do just that, creating a disconnect between data science teams and IT/DevOps when it comes to AI development. Great teams incorporate a variety of skill sets.

Artificial Intelligence 343

Artificial Intelligence Artificial Inteligence DevOps Sport 343

Trigent

JUNE 20, 2022

Businesses worldwide are realizing the importance of the considerable volume of data they possess and the need to extract value from it and incorporate it into enhancing Customer Experience or simplifying operational processes for improved results. This is where data engineering services providers come into play.

Data Engineering 52

Data Engineering Engineering Data Strategy 52

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.

Machine Learning 133

Machine Learning Artificial Inteligence Data Applications 133

TechCrunch

NOVEMBER 28, 2022

Artificial intelligence promises to help, and maybe even replace, humans to carry out everyday tasks and solve problems that humans have been unable to tackle, yet ironically, building that AI faces a major scaling problem. It has effectively built training models to automate the training of those models.

Training 240

Training Data Technical Review Artificial Inteligence 240

Cloudera

NOVEMBER 19, 2021

We are excited by the endless possibilities of machine learning (ML). We recognise that experimentation is an important component of any enterprise machine learning practice. Organizations need to usher their ML models out of the lab (i.e., COPML accounts for the fact that true production machine learning (i.e.,

Machine Learning 124

Machine Learning Artificial Inteligence eBook Sustainability 124

Confluent

FEBRUARY 6, 2019

Building a scalable, reliable and performant machine learning (ML) infrastructure is not easy. It takes much more effort than just building an analytic model with Python and your favorite machine learning framework. Impedance mismatch between data scientists, data engineers and production engineers.

Machine Learning 107

Machine Learning Artificial Inteligence Scalability Data Engineering 107

CIO

AUGUST 2, 2023

A data and analytics capability cannot emerge from an IT or business strategy alone. With both technology and business organization deeply involved in the what, why, and how of data, companies need to create cross-functional data teams to get the most out of it. What are some examples of data solutions in each of those buckets?

Data 243

Data Architecture Government Strategy 243

DataRobot

MARCH 10, 2022

This “revolution” stems from breakthrough advancements in artificial intelligence, robotics, and the Internet of Things (IoT). These initiatives utilize interconnected devices and automated machines that create a hyperbolic increase in data volumes. High-level example of a common machine learning lifecycle.

Artificial Inteligence 52

Artificial Inteligence Artificial Intelligence Machine Learning IoT 52

TechCrunch

APRIL 26, 2021

Faculty , a VC-backed artificial intelligence startup, has won a tender to work with the NHS to make better predictions about its future requirements for patients, based on data drawn from how it handled the COVID-19 pandemic. Palantir doesn’t really do AI, they do data engineering in a big way.

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Artificial Inteligence Artificial Intelligence Machine Learning Scalability 231

CIO

FEBRUARY 13, 2023

This includes spending on strengthening cybersecurity (35%), improving customer service (32%) and improving data analytics for real-time business intelligence and customer insight (30%). Cold: On-prem infrastructure As they did in 2022, many IT leaders are reducing investments in data centers and on-prem technologies. “We

Budget 363

Budget Artificial Inteligence Technical Review VR 363

Netflix Tech

JUNE 1, 2021

Data Engineers of Netflix?—?Interview Interview with Samuel Setegne Samuel Setegne This post is part of our “Data Engineers of Netflix” interview series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. For example?—?clinical

Data Engineering 52

Data Engineering Engineering Data Culture 52

TechCrunch

APRIL 12, 2022

While companies find AI’s predictive power alluring, particularly on the data analytics side of the organization, achieving meaningful results with AI often proves to be a challenge. It’s true that AI can help to project revenue, for example, by identifying trends in buying and selling. ” Taking Flyte.

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Artificial Inteligence Machine Learning Open Source Biotech 202

TechCrunch

MAY 3, 2022

“There were no purpose-built machine learning data tools in the market, so [we] started Galileo to build the machine learning data tooling stack, beginning with a [specialization in] unstructured data,” Chatterji told TechCrunch via email.

Artificial Inteligence 223

Artificial Inteligence Machine Learning Development Software Review 223

Cloudera

OCTOBER 19, 2021

Airflow has been adopted by many Cloudera Data Platform (CDP) customers in the public cloud as the next generation orchestration service to setup and operationalize complex data pipelines. A simple example of this would be parameterizing SQL query within the CDW operator. Easing development friction.

Data Engineering 119

Data Engineering Engineering Data Virtualization 119

Cloudera

JANUARY 20, 2021

to make a classification model based off of training data stored in both Cloudera’s Operational Database (powered by Apache HBase) and Apache HDFS. Afterwards, this model is then scored and served through a simple Web Application. Machine learning is now being used to solve many real-time problems.

Machine Learning 113

Machine Learning Artificial Inteligence Applications Data 113

Cloudera

APRIL 30, 2021

Apache Spark is now widely used in many enterprises for building high-performance ETL and Machine Learning pipelines. Cloudera Data Engineering (CDE) is a cloud-native service purpose-built for enterprise data engineering teams. Here is an example showing a simple PySpark program querying an ACID table.

Data Engineering 63

Data Engineering Engineering Data Software Review 63

O'Reilly Media - Ideas

NOVEMBER 13, 2018

Considerations for a world where ML models are becoming mission critical. In this post, I share slides and notes from a keynote I gave at the Strata Data Conference in New York last September. As the data community begins to deploy more machine learning (ML) models, I wanted to review some important considerations.

Machine Learning 92

Machine Learning Artificial Inteligence Software Review Conference 92

CIO

JULY 18, 2023

The CIO’s biggest hiring challenge is clear: “There is simply not enough talent to go around,” says Scott duFour, global CIO of business payments company Fleetcor, for whom positions in areas such as AI, cloud architecture, and data science remain the toughest to fill. S&P Global, for example, is entering its AI 2.0 The net result?

Technical Advisors 246

Technical Advisors Artificial Inteligence Generative AI How To 246

Altexsoft

MAY 27, 2020

Machine learning (ML) history can be traced back to the 1950s, when the first neural networks and ML algorithms appeared. Analysis of more than 16.000 papers on data science by MIT technologies shows the exponential growth of machine learning during the last 20 years pumped by big data and deep learning advancements.

Machine Learning 89

Machine Learning Artificial Inteligence Architecture Training 89

O'Reilly Media - Ideas

AUGUST 18, 2020

So you need to redesign your company’s data infrastructure. That is, products that are laser-focused on one aspect of the data science and machine learning workflows, in contrast to all-in-one platforms that attempt to solve the entire space of data workflows. The Two Cultures of Data Tooling.

Machine Learning 144

Machine Learning Artificial Inteligence Data Data Engineering 144

Honeycomb

FEBRUARY 20, 2024

It was difficult in lots of different ways, but one thing I didn’t elaborate on in several blog posts was how lucky I was to have a coherent way to get the data I needed to make the feature useful for users. The other “half” of the equation is having the right data to feed into the model to handle the use cases your users expect.

Data 64

Data Artificial Inteligence Weak Development Team Examples 64