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

O'Reilly Media - Ideas

FEBRUARY 11, 2019

Highlights and use cases from companies that are building the technologies needed to sustain their use of analytics and machine learning. Profiles of IT executives suggest that many are planning to spend significantly in cloud computing and AI over the next year. AI and machine learning in the enterprise.

Big Data 87

Big Data Technology Tools Cloud 87

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

CIO

JUNE 7, 2022

Predictive analytics applies techniques such as statistical modeling, forecasting, and machine learning to the output of descriptive and diagnostic analytics to make predictions about future outcomes. In business, predictive analytics uses machine learning, business rules, and algorithms.

Analytics 338

Analytics Data Analysis Business Analytics 338

CTOvision

MAY 1, 2014

Senior Software Engineer – Big Data. IO is the global leader in software-defined data centers. IO has pioneered the next-generation of data center infrastructure technology and Intelligent Control, which lowers the total cost of data center ownership for enterprises, governments, and service providers.

Big Data 107

Big Data Data Engineering Engineering Data Center 107

CIO

DECEMBER 16, 2022

The top-earning skills were big data analytics and Ethereum, with a pay premium of 20% of base salary, both up 5.3% Other non-certified skills attracting a pay premium of 19% included data engineering , the Zachman Framework , Azure Key Vault and site reliability engineering (SRE). in the previous six months.

Technical Review 246

Technical Review Analytics AWS SCRUM 246

TechCrunch

APRIL 11, 2023

CEO Tatiana Krupenya says that it’s an administrative tool that allows anyone to access data from a variety of sources. Krupenya says this capability puts data administration in reach of not just the most technical data engineers, but also people in other lines of business roles, who normally might not have access to tools like this. “So

Open Source 203

Open Source Database Administration Machine Learning Artificial Inteligence 203

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. “By with Spark 3.0

Enterprise 92

Enterprise Cloud Data Machine Learning 92

ParkMyCloud

DECEMBER 11, 2020

If you’re looking to break into the cloud computing space, or just continue growing your skills and knowledge, there are an abundance of resources out there to help you get started, including free Google Cloud training. Google Cloud Free Program. As a new Google Cloud customer, you can get started with a 90-day free trial.

Google Cloud 97

Google Cloud Training Resources Cloud 97

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

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 119

Artificial Inteligence Generative AI Security Applications 119

Hu's Place - HitachiVantara

NOVEMBER 11, 2018

Forbes believes it is an imperative for CIOs to view cloud computing as a critical element of their competitiveness. Cloud-based spending will reach 60% of all IT infrastructure and 60-70% of all software, services, and technology spending by 2020.

Cloud 78

Cloud Google Cloud Azure AWS 78

Hu's Place - HitachiVantara

APRIL 11, 2019

Few Data Management Frameworks are Business Focused Data management has been around since the beginning of IT, and a lot of technology has been focused on big data deployments, governance, best practices, tools, etc. However, large data hubs over the last 25 years (e.g., What has changed since then?

Data Engineering 81

Data Engineering Machine Learning Artificial Inteligence Technical Review 81

CIO

JULY 14, 2023

A general LLM won’t be calibrated for that, but you can recalibrate it—a process known as fine-tuning—to your own data. Fine-tuning applies to both hosted cloud LLMs and open source LLM models you run yourself, so this level of ‘shaping’ doesn’t commit you to one approach. If you’re not using it, you’re going to get left behind.”

Generative AI 246

Generative AI Artificial Inteligence Open Source ChatGPT 246

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

Cloudera

JUNE 7, 2022

Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB. In fact, the total amount of data is expected to nearly triple by 2025. Big data is cool again. As the company who taught the world the value of big data, we always knew it would be.

Data 112

Data Architecture Analytics Government 112

Apiumhub

JUNE 22, 2021

Same as last year, the event offers six workshops (crash-course) themes, each dedicated to a unique domain area: Data-driven Strategy, Analytics & Visualisation, Machine Learning, IoT Analytics & Data Management, Data Management and Data Engineering.

Innovation 84

Innovation Data Technical Review Artificial Inteligence 84

Cloudera

JANUARY 19, 2018

Machine Learning in the Age of Big Data. Sean Anderson provides a tutorial on machine learning. From its origins in the 1950’s to today, the age of big data. Sean ascertains that larger data sets and increased access to compute power is propelling the adoption of machine learning.

Artificial Inteligence 46

Artificial Inteligence Machine Learning Big Data IoT 46

CTOvision

JUNE 15, 2015

They also launched a plan to train over a million data scientists and data engineers on Spark. At the core of this commitment, IBM plans to embed Spark into its industry-leading Analytics and Commerce platforms, and to offer Spark as a service on IBM Cloud. IBM has been a decades long leader in open source innovation.

Open Source 117

Open Source Big Data Machine Learning Artificial Inteligence 117

Cloudera

DECEMBER 17, 2021

As a Principal Solutions Engineer, he says his core responsibility is “to take Cloudera’s latest and greatest technology and meet a customer’s complex business requirements, across the data lifecycle, on any cloud or the datacenter.”. As he puts it, “Cloudera puts the customers first”.

Engineering 95

Engineering Telecommunications Culture Machine Learning 95

Hu's Place - HitachiVantara

JANUARY 3, 2019

Public cloud, agile methodologies and devops, RESTful APIs, containers, analytics and machine learning are being adopted. ” Deployments of large data hubs have only resulted in more data silos that are not easily understood, related, or shared.

Trends 86

Trends Artificial Inteligence Data Center Machine Learning 86

Cloudera

SEPTEMBER 10, 2021

By more effectively leveraging its petabytes of current and historical data, the IRS is working to stave off costly fraud and waste, more efficiently deliver on fundamental missions, and better protect taxpayers, including from risks such as identity theft. Pairing High-Tech Keys to Unlock the Power of Data.

Artificial Inteligence 69

Artificial Inteligence Machine Learning Artificial Intelligence Engineering 69

Mobilunity

MAY 8, 2023

Here collected data from databases, logs, IoT devices, social media, and other sources. Storage zone is where the raw data is stored in its original format. The storage zone may use a distributed file system such as Hadoop Distributed File System (HDFS) or cloud-based storage. Cost Savings. Scalability.

Engineering 52

Engineering Data Storage AWS 52

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 cloud native table format was open sourced into Apache Iceberg by its creators.

Data 93

Data Analytics Open Source Architecture 93

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 68

Course Training Artificial Inteligence Software Review 68

Cloudera

JANUARY 20, 2021

Most of what is written though has to do with the enabling technology platforms (cloud or edge or point solutions like data warehouses) or use cases that are driving these benefits (predictive analytics applied to preventive maintenance, financial institution’s fraud detection, or predictive health monitoring as examples) not the underlying data.

Data 109

Data Artificial Inteligence Analytics Machine Learning 109

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 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 50

Course Training Artificial Inteligence Software Review 50

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

Existek

JANUARY 11, 2022

Why is cloud computing better than traditional on-premise environments? How to select the right cloud service provider? It’ll be interesting to discover how market-leading providers set new standards and alter approaches to cloud computing. Cloud solutions have become unquestionably crucial for many industries and businesses.

Azure 52

Azure AWS Cloud How To 52

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 46

Course Training Artificial Inteligence Machine Learning 46

Cloudera

AUGUST 31, 2021

The key questions that need to be answered are: Do you have workloads you wish would run faster, but you just can’t make it happen without an expensive solution from your existing data warehouse? Are you looking for your data warehouse to support the hybrid multi-cloud? Copyright © 2021 Accenture. All rights reserved.

Data 84

Data Analytics Cloud Technical Review 84

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

MAY 10, 2018

Click to tweet : Nominations are now open for the sixth annual Cloudera Data Impact Awards! With advancements in exploratory data science, machine learning, predictive analytics, AI, and data engineering, the world is increasingly driven by data. Enterprise machine learning.

Data 41

Data Machine Learning Artificial Inteligence Data Engineering 41

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 Visualization. Data Training. Agriculture.

Data 52

Data How To Machine Learning Artificial Inteligence 52

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. CONS This will trigger a full read and write of the data and it might be an expensive operation. Your entire data set will be duplicated.

Backup 72

Backup Data Engineering Engineering Data 72

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. The production environment has a predefined configuration.

DevOps 130

DevOps Data Analytics Policies 130