CTOvision

FEBRUARY 23, 2017

This is the place to dive deep into the latest on Big Data, Analytics, Artificial Intelligence, IoT, and the massive cybersecurity issues in all those topics. You'll dissect case studies, develop new skills through in-depth tutorials, share emerging best practices in data science, and imagine the future.

Big Data 61

Big Data Artificial Intelligence Artificial Inteligence Case Study 61

Apiumhub

APRIL 1, 2021

Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data by by EMC Education Services. The whole data analytics lifecycle is explained in detail along with case study and appealing visuals so that you can see the practical working of the entire system.

Artificial Inteligence 52

Artificial Inteligence Data Handbook Machine Learning 52

Cloudera

AUGUST 31, 2021

Data warehousing is the backbone of every data driven organization , providing mission critical analytics. Today, modern data warehousing has evolved to meet the intensive demands of the newest analytics required for a business to be data driven. Copyright © 2021 Accenture. All rights reserved.

Data 80

Data Analytics Cloud Technical Review 80

Altexsoft

APRIL 13, 2023

The annual IHS Markit Supply Chain Survey Report found that 63 percent of companies don’t have sufficient technology to approach their top priority optimization strategy, i.e., spend analytics (the situation within other strategic areas is similar). It also often includes analytics, reporting, and forecasting capabilities.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

Netflix Tech

MARCH 5, 2019

While our engineering teams have and continue to build solutions to lighten this cognitive load (better guardrails, improved tooling, …), data and its derived products are critical elements to understanding, optimizing and abstracting our infrastructure. What will be the cost of rolling out the winning cell of an AB test to all users?

Infrastructure 73

Infrastructure Scalability Cloud Data 73

Altexsoft

JUNE 11, 2021

Process analytics takes place. Here, KPIs can be created and monitored to uncover potential improvement areas, data mining and/or ML algorithms can be used to detect hidden patterns and dependencies, or conformance checking techniques can be applied to compare the process to a certain ideal model. Consider predictive analytics.

Applications 69

Applications Weak Development Team Systems Review Software Review 69

O'Reilly Media - Ideas

JUNE 4, 2019

Fundamentals of Machine Learning and Data Analytics , July 10-11. Essential Machine Learning and Exploratory Data Analysis with Python and Jupyter Notebook , July 11-12. Real-Time Streaming Analytics and Algorithms for AI Applications , July 17. Data science and data tools. Debugging Data Science , June 26.

Course 64

Course Training Artificial Inteligence Software Review 64

Kentik

MAY 23, 2017

Imagine a big data time-series datastore that unifies traffic flow records (NetFlow, sFlow, IPFIX) with related data such as BGP routing, GeoIP, network performance, and DNS logs, that retains unsummarized data for months, and that has the compute and storage power to answer ad hoc queries across billions of data points in a couple of seconds.

Network 40

Network Open Source Big Data Load Balancer 40

O'Reilly Media - Ideas

JUNE 5, 2019

Fundamentals of Machine Learning and Data Analytics , July 10-11. Essential Machine Learning and Exploratory Data Analysis with Python and Jupyter Notebook , July 11-12. Real-Time Streaming Analytics and Algorithms for AI Applications , July 17. Data science and data tools. Debugging Data Science , June 26.

Course 49

Course Training Artificial Inteligence Software Review 49

CIO

AUGUST 18, 2022

Previously, Walgreens was attempting to perform that task with its data lake but faced two significant obstacles: cost and time. Those challenges are well-known to many organizations as they have sought to obtain analytical knowledge from their vast amounts of data. You can intuitively query the data from the data lake.

Data 350

Data Artificial Inteligence Technical Advisors Technical Review 350

Apiumhub

APRIL 5, 2022

Apiumhub has become a Media partner of the Data Innovation Summit – the most influential data, AI and advanced analytics event in the Nordics and beyond. . Data Innovation Summit speakers dive directly into the topic and focus on the key learning points. Save the dates: 5th & 6th May, 2022. .

Innovation 52

Innovation Data Artificial Inteligence Case Study 52

Exadel

AUGUST 26, 2020

Data Analytics for Better Business Intelligence. Data is king in the modern business world. Thanks to technology, collecting data from just about any aspect of a business is possible — including tracking customers’ activity, desires and frustrations while using a product or service. Types of Data Analytics.

Analytics 52

Analytics Data How To Machine Learning 52

Perficient

APRIL 1, 2024

Case Study A private equity organization wants to have a close eye on equity stocks it has invested in for their clients. They want to generate trends, predictions (using ML), and analyze data based on algorithms developed by their portfolio management team in collaboration with data scientists written in Python.

Data 64

Data Azure Case Study Data Engineering 64

Altexsoft

MARCH 31, 2020

It means you must collect transactional data and move it from the database that supports transactions to another system that can handle large volumes of data. Only after these actions can you analyze data with dedicated software (a so-called online analytical processing or OLAP system). But how do you move data?

Data 76

Data Storage Analytics Data Center 76

TIBCO - Connected Intelligence

NOVEMBER 4, 2019

TDWI Munich , with thousands of attendees and nearly a hundred sponsors, is Germany’s premier annual data and analytics event. While there, I took advantage of the opportunity to do some informal market research on data and analytics trends. TIBCO’s Partners are All In for Data Virtualization.

Virtualization 4

Virtualization Artificial Inteligence Data Artificial Intelligence 4

Cloudera

APRIL 21, 2022

Its evolution to the present-day cloud-based package is a real-world case study that will likely live in IT textbooks for as long as use cases will be referenced. . MHS Genesis has to tackle an almost impossible job in moving and processing petabytes of data, securely and accurately.

Security 83

Security Data Insurance System 83

Altexsoft

DECEMBER 9, 2020

In the era of global digital transformation , the role of data analysis in decision-making increases greatly. Still, today, according to Deloitte research, insight-driven companies are fewer than those not using an analytical approach to decision-making, even though the majority agrees on its importance. Stages of analytics maturity.

Analytics 102

Analytics Technical Review Technology Applications 102

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

Kentik

OCTOBER 25, 2016

Since most traditional tools rely on separate tables to track monitoring data for different purposes, there are hard limits to how “wide” of a dataset can be handled by a given table and its corresponding monitoring process. That encourages the segmentation of data into more predictable buckets. Deep analytics.

Scalability 40

Scalability Architecture Big Data Analytics 40

Agile Engine

DECEMBER 27, 2023

From emerging trends to hiring a data consultancy, this article has everything you need to navigate the data analytics landscape in 2024. What is a data analytics consultancy? Big data consulting services 5. 4 types of data analysis 6. Data analytics use cases by industry 7.

Big Data 52

Big Data Analytics Data Analysis 52

Datavail

SEPTEMBER 8, 2022

According to an IDG survey , companies now use an average of more than 400 different data sources for their business intelligence and analytics processes. What’s more, 20 percent of these companies are using 1,000 or more sources, far too many to be properly managed by human data engineers.

Data 40

Data Nonprofit Quality Assurance Education 40