Cloudera

OCTOBER 4, 2023

And all of this should ideally be delivered in an easy to deploy and administer data platform available to work in any cloud. This is especially necessary when combining real-time data with prepared data, and adding predictive concepts into our augmented dashboards and reports.

Analytics 87

Analytics Machine Learning Artificial Inteligence Telecommunications 87

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

The Accidental Successful CIO

MAY 12, 2021

Understanding Business Intelligence vs. Business Analytics. Business intelligence tools provide insights into the current state of the business or organization: where are sales prospects in the pipeline today? It also gets to the heart of the question of who business intelligence is designed for.

Business Intelligence 90

Business Intelligence Business Analytics Analytics Off-The-Shelf 90

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

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 51

Course Training Artificial Inteligence Software Review 51

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

Cloudera

DECEMBER 21, 2020

Company data exists in the data lake. Data Catalog profilers have been run on existing databases in the Data Lake. A Cloudera Machine Learning Workspace exists . A Cloudera Data Warehouse virtual warehouse with Cloudera Data Visualisation enabled exists. The Data Scientist.

Data 97

Data Virtualization Banking Data Engineering 97

Cloudera

FEBRUARY 22, 2021

This category describes the unique ability of CDP to accelerate deployment of use cases (and, as a result, the associated business value) by: . without integration delays or having to deal with fragmented data silos that result in operational inefficiencies. .

Data 79

Data Analytics Government Technical Review 79

Altexsoft

FEBRUARY 8, 2021

To support the planning process, predictive analytics and machine learning (ML) techniques can be implemented. We have previously described demand forecasting methods and the role of machine learning solutions in a dedicated article. Today, consumers’ preferences are changing momentarily and often chaotically.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

O'Reilly Media - Ideas

MARCH 1, 2023

Content about software development was the most widely used (31% of all usage in 2022), which includes software architecture and programming languages. Software development is followed by IT operations (18%), which includes cloud, and by data (17%), which includes machine learning and artificial intelligence.

Trends 137

Trends Technical Review Technology Software Review 137

Apiumhub

AUGUST 12, 2021

This year you will have 6 unique tracks: Cloud Computing: IaaS, PaaS, SaaS DevOps: Microservices, Automation, ASRs Cybersecurity: Threats, Defenses, Tests Data Science: ML, AI, Big Data, Business Analytics Programming languages: C++, Python, Java, Javascript,Net Future & Inspire: Mobility, 5G data networks, Diversity, Blockchain, VR.

Industry 59

Industry Technical Advisors CTO Coach Azure 59

Altexsoft

JANUARY 14, 2021

What specialists and their expertise level are required to handle a data warehouse? However, all of the warehouse products available require some technical expertise to run, including data engineering and, in some cases, DevOps. Is it a flat-rate or on-demand model? Snowflake is also a good choice for data streaming.

Backup 115

Backup Azure Software Review Systems Review 115

Cloudera

NOVEMBER 2, 2020

These include stream processing/analytics, batch processing, tiered storage (i.e. for active archive or joining live data with historical data), or machine learning. Architecture for Real-Time Data Warehousing with Extended Capabilities. Data Hub – . Data Hub – .

Data 94

Data Analytics Storage Big Data 94

O'Reilly Media - Ideas

SEPTEMBER 11, 2019

Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena.

Conference 8

Conference Data Data Engineering Artificial Inteligence 8