CIO

JUNE 7, 2022

Data analytics has become increasingly important in the enterprise as a means for analyzing and shaping business processes and improving decision-making and business results. Diagnostic analytics uses data (often generated via descriptive analytics) to discover the factors or reasons for past performance.

Analytics 334

Analytics Data Analysis Business Analytics 334

d2iq

FEBRUARY 19, 2021

Going from a prototype to production is perilous when it comes to machine learning: most initiatives fail , and for the few models that are ever deployed, it takes many months to do so. As little as 5% of the code of production machine learning systems is the model itself. Adapted from Sculley et al.

Artificial Inteligence 103

Artificial Inteligence Machine Learning Technical Review Software Review 103

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

CIO

FEBRUARY 14, 2023

To succeed with real-time AI, data ecosystems need to excel at handling fast-moving streams of events, operational data, and machine learning models to leverage insights and automate decision-making. report they have established a data culture 26.5% report they have a data-driven organization 39.7%

Artificial Inteligence 281

Artificial Inteligence Strategy Data Machine Learning 281

CIO

SEPTEMBER 2, 2022

This uniquely skilled, relatively new breed of data experts gathers and analyzes data — both structured and unstructured — to solve real business problems, using statistics, machine learning, algorithms, and natural language processing. Gartner reported that a data scientist in Washington, D.C.,

Data 246

Data Machine Learning Artificial Inteligence Training 246

CIO

SEPTEMBER 1, 2022

This uniquely skilled, relatively new breed of data experts gathers and analyzes data — both structured and unstructured — to solve real business problems, using statistics, machine learning, algorithms, and natural language processing. Gartner reported that a data scientist in Washington, D.C.,

Data 246

Data Machine Learning Artificial Inteligence Training 246

Altexsoft

FEBRUARY 11, 2023

The 11th annual survey of Chief Data Officers (CDOs) and Chief Data and Analytics Officers reveals 82 percent of organizations are planning to increase their investments in data modernization in 2023. What’s more, investing in data products, as well as in AI and machine learning was clearly indicated as a priority.

Data 87

Data Data Engineering Big Data Architecture 87

O'Reilly Media - Data

APRIL 11, 2018

It’s important to understand the differences between a data engineer and a data scientist. Misunderstanding or not knowing these differences are making teams fail or underperform with big data. I think some of these misconceptions come from the diagrams that are used to describe data scientists and data engineers.

Data Engineering 280

Data Engineering Engineering Data Artificial Inteligence 280

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. and NVIDIA RAPIDS and AI offer data engineers a potential 3-10x performance improvement for workloads including ETL and SQL-heavy data analysis.

Enterprise 94

Enterprise Cloud Data Machine Learning 94

AWS Machine Learning - AI

JANUARY 26, 2024

The goal of this post is to empower AI and machine learning (ML) engineers, data scientists, solutions architects, security teams, and other stakeholders to have a common mental model and framework to apply security best practices, allowing AI/ML teams to move fast without trading off security for speed.

Artificial Inteligence 115

Artificial Inteligence Generative AI Security Applications 115

Hacker Earth Developers Blog

JUNE 26, 2019

Data science is an interdisciplinary field that uses a blend of data inference and algorithm development to solve complex analytical problems. An ideal candidate has skills in the 3 fields: mathematics/ statistics/ machine learning/ programming and business/ domain knowledge. . Machine Learning and Programming.

Data 200

Data How To Recruiting Machine Learning 200

Hu's Place - HitachiVantara

MAY 10, 2019

Rule-based fraud detection software is being replaced or augmented by machine-learning algorithms that do a better job of recognizing fraud patterns that can be correlated across several data sources. DataOps is required to engineer and prepare the data so that the machine learning algorithms can be efficient and effective.

Data 90

Data Machine Learning Artificial Inteligence Weak Development Team 90

CTOvision

JUNE 15, 2015

For years it has seemed like IBM was giving lip-service to Spark while emphasizing capabilities that they placed big bets on over the years (especially IBM's flagship stream processing product, InfoSphere Streams). Spark is still new and frankly there have been issues with performance from time to time.

Open Source 117

Open Source Big Data Machine Learning Artificial Inteligence 117

Altexsoft

AUGUST 25, 2020

Big data can be quite a confusing concept to grasp. What to consider big data and what is not so big data? Big data is still data, of course. But it requires a different engineering approach and not just because of its amount. Data engineering vs big data engineering.

Big Data 75

Big Data Data Engineering Engineering Data 75

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. The post The Future of the Data Lakehouse – Open appeared first on Cloudera Blog.

Data 94

Data Analytics Open Source Architecture 94

Mobilunity

MAY 8, 2023

This includes data cleansing, normalization, and enrichment. Analytics zone is where data analysts and data scientists can access the data to perform queries, generate reports, and create models. The analytics zone may include tools for data visualization, machine learning, and predictive analytics.

Engineering 52

Engineering Data Storage AWS 52

Hacker Earth Developers Blog

JUNE 26, 2019

Data science is an interdisciplinary field that uses a blend of data inference and algorithm development to solve complex analytical problems. An ideal candidate has skills in the 3 fields: mathematics/ statistics/ machine learning/ programming and business/ domain knowledge. . Machine Learning and Programming.

Data 100

Data How To Recruiting Machine Learning 100

CIO

JULY 14, 2023

Generative AI models like ChatGPT and GPT4 with a plugin model let you augment the LLM by connecting it to APIs that retrieve real-time information or business data from other systems, add other types of computation, or even take action like open a ticket or make a booking.

Generative AI 237

Generative AI Artificial Inteligence Open Source ChatGPT 237

Altexsoft

AUGUST 29, 2023

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

Architecture 52

Architecture Data Storage Machine Learning 52

O'Reilly Media - Ideas

JUNE 4, 2019

Get hands-on training in Docker, microservices, cloud native, Python, machine learning, and many other topics. Learn new topics and refine your skills with more than 219 new live online training courses we opened up for June and July on the O'Reilly online learning platform. AI and machine learning.

Course 66

Course Training Artificial Inteligence Software Review 66

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. Ingest Data.

Machine Learning 138

Machine Learning Artificial Inteligence Engineering Training 138

Apiumhub

APRIL 1, 2021

Learning data science through books will help you get a holistic view of Data Science as data science is not just about computing, it also includes mathematics, probability, statistics, programming, machine learning, and much more. Top Data science books you should definitely read.

Artificial Inteligence 52

Artificial Inteligence Data Handbook Machine Learning 52

Hu's Place - HitachiVantara

NOVEMBER 11, 2018

REAN Cloud is a global cloud systems integrator, managed services provider and solutions developer of cloud-native applications across big data, machine learning and emerging internet of things (IoT) spaces. This April, 47Lining, announced its Amazon Web Services (AWS) Industrial Time Series Data Connector Quick Start.

Cloud 78

Cloud Google Cloud Azure AWS 78

Altexsoft

OCTOBER 30, 2021

If you’re an executive who has a hard time understanding the underlying processes of data science and get confused with terminology, keep reading. We will try to answer your questions and explain how two critical data jobs are different and where they overlap. Data science vs data engineering.

Data Engineering 98

Data Engineering Engineering Data Machine Learning 98

Cloudera

JULY 14, 2023

Introduction For more than a decade now, the Hive table format has been a ubiquitous presence in the big data ecosystem, managing petabytes of data with remarkable efficiency and scale. Depending on the size and usage patterns of the data, several different strategies could be pursued to achieve a successful migration.

Backup 71

Backup Data Engineering Engineering Data 71

O'Reilly Media - Ideas

JUNE 5, 2019

Get hands-on training in Docker, microservices, cloud native, Python, machine learning, and many other topics. Learn new topics and refine your skills with more than 219 new live online training courses we opened up for June and July on the O'Reilly online learning platform. AI and machine learning.

Course 49

Course Training Artificial Inteligence Software Review 49

O'Reilly Media - Ideas

APRIL 9, 2019

A few months ago, I wrote about the differences between data engineers and data scientists. An interesting thing happened: the data scientists started pushing back, arguing that they are, in fact, as skilled as data engineers at data engineering. I agree; learn as much as you can.

Data Engineering 111

Data Engineering Engineering Data Technical Review 111

Trigent

NOVEMBER 3, 2022

Experts unanimously agree data analytics is here to stay, considering 98% of 3PLs and 93% of shippers believe in having data-driven decision-making capabilities to manage supply chain activities. In comparison, 71% of 3PLs think process quality and performance can be significantly improved with the help of big data.

Analytics 52

Analytics Data IoT Trends 52

Mobilunity

DECEMBER 21, 2022

Tech companies use data science to enhance user experience, create personalized recommendation systems, develop innovative solutions, and more. Data science in agriculture can help businesses develop data pipelines specifically for automation and fast scalability. Data Preparation. Data Modeling. Agriculture.

Data 52

Data How To Machine Learning Artificial Inteligence 52

Cloudera

JANUARY 20, 2021

Predictive Analytics – predictive analytics based upon AI and machine learning (Fraud detection, predictive maintenance, demand based inventory optimization as examples). Security & Governance – an integrated set of security, management and governance technologies across the entire data lifecycle.

Data 110

Data Artificial Inteligence Analytics Machine Learning 110

O'Reilly Media - Ideas

MAY 1, 2019

Get hands-on training in machine learning, blockchain, cloud native, PySpark, Kubernetes, and many other topics. Learn new topics and refine your skills with more than 160 new live online training courses we opened up for May and June on the O'Reilly online learning platform. AI and machine learning.

Course 45

Course Training Artificial Inteligence Machine Learning 45

Xebia

MARCH 10, 2021

Figure 1 shows the skills of a typical data scientist. However, the ‘Computer Science & IT’ skills are ok for the Machine Learning part, but the Software Development skills of a Data Scientist are focussed on the creation of the advanced analytics model. There are many meanings associated with the term DevOps.

DevOps 130

DevOps Data Analytics Policies 130

Altexsoft

APRIL 22, 2020

So, along with data scientists who create algorithms, there are data engineers, the architects of data platforms. In this article we’ll explain what a data engineer is, the field of their responsibilities, skill sets, and general role description. What is a data engineer?

Data Engineering 69

Data Engineering Engineering Artificial Inteligence Data 69

Altexsoft

JULY 18, 2023

These seemingly unrelated terms unite within the sphere of big data, representing a processing engine that is both enduring and powerfully effective — Apache Spark. Maintained by the Apache Software Foundation, Apache Spark is an open-source, unified engine designed for large-scale data analytics.

Weak Development Team 52

Weak Development Team Big Data Data Machine Learning 52

Altexsoft

JUNE 26, 2023

While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection?

Machine Learning 52

Machine Learning Artificial Inteligence Data Systems Review 52

Cloudera

MAY 22, 2018

With Experiments, data scientists can run a batch job that will: create a snapshot of model code, dependencies, and configuration parameters necessary to train the model. track model metrics, performance, and any model artifacts the user specifies. for the Oracle Big Data Appliance). or higher 5.x or higher 5.x

Data 41

Data Load Balancer Machine Learning Artificial Inteligence 41

Altexsoft

JUNE 25, 2019

Being at the top of data science capabilities, machine learning and artificial intelligence are buzzing technologies many organizations are eager to adopt. 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.

Data Engineering 106

Data Engineering Engineering Data Artificial Inteligence 106