CIO

OCTOBER 7, 2022

With data increasingly vital to business success, business intelligence (BI) continues to grow in importance. With a strong BI strategy and team, organizations can perform the kinds of analysis necessary to help users make data-driven business decisions. BI encompasses numerous roles.

Business Intelligence 363

Business Intelligence Business Analytics Analytics Analysis 363

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. Real-Time Streaming Analytics and Algorithms for AI Applications , July 17.

Course 65

Course Training Artificial Inteligence Software Review 65

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. Real-Time Streaming Analytics and Algorithms for AI Applications , July 17.

Course 49

Course Training Artificial Inteligence Software Review 49

CTOvision

OCTOBER 18, 2013

With the continuous development of advanced infrastructure based around Apache Hadoop there has been an incredible amount of innovation around enterprise “Big Data” technologies, including in the analytical tool space. Which firms have something so important that you should push hard to get them into your enterprise?

Technical Review 99

Technical Review Analytics Technology Big Data 99

Altexsoft

FEBRUARY 8, 2021

For example, you can see that the machine breakdown increased, and the root cause analysis shows that it happened because of cheaper spare parts or fuel. More advanced analytics enable conducting preventive or predictive maintenance based on data from IoT devices and various sensors connected to equipment. Cost control.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

Infinidat

MARCH 10, 2021

With digital transformation under way at most enterprises, IT management is pondering how to optimize storage infrastructure to best support the new big data analytics focus. Wed, 03/10/2021 - 12:42. Guest Blogger: Eric Burgener, Research Vice President, Infrastructure Systems, Platforms and Technologies, IDC.

Business Intelligence 98

Business Intelligence Storage Infrastructure Artificial Inteligence 98

Altexsoft

JANUARY 14, 2021

You may also find it under the name of an enterprise data warehouse (EDW). It is usually created and used primarily for data reporting and analysis purposes. Summarized touches upon the fact the data is used for data analytics. Scalability opportunities. Scalability. Data warehouse architecture.

Backup 115

Backup Azure Software Review Systems Review 115

Cloudera

NOVEMBER 2, 2020

Conventional enterprise data types. a data mart) or more comprehensively as an Enterprise Data Warehouse. Sometimes you know that there is always a time element to the data events and to the analysis, and you know in advance the types of queries your users will run. Flexible, scalable query engine for EDW. Data Model.

Data 95

Data Analytics Storage Big Data 95

Altexsoft

NOVEMBER 23, 2021

Not to mention that additional sources are constantly being added through new initiatives like big data analytics , cloud-first, and legacy app modernization. To break data silos and speed up access to all enterprise information, organizations can opt for an advanced data integration technique known as data virtualization.

Virtualization 69

Virtualization Tools Data Architecture 69

O'Reilly Media - Ideas

MARCH 1, 2023

Decomposing a complex monolith into a complex set of microservices is a challenging task and certainly one that can’t be underestimated: developers are trading one kind of complexity for another in the hope of achieving increased flexibility and scalability long-term. Data engineering was the dominant topic by far, growing 35% year over year.

Trends 134

Trends Technical Review Technology Software Review 134

Sunflower Lab

APRIL 2, 2024

From unraveling the essence of predictive analytics to the intricacies of turning data points into dollar signs, this comprehensive guide will prime you for a predictive power play that resonates throughout your enterprise. This scalability allows organizations to grow their predictive models without fear of hitting a performance wall.

Analytics 40

Analytics Machine Learning Artificial Inteligence Analysis 40

Altexsoft

FEBRUARY 3, 2020

Data Analytics Definition, Stats, and Benefits. Before we show you the best data analytics tools, we want to help you to understand why businesses need such platforms in the first place. More than 150 zettabytes (150 trillion gigabytes) of data will need analysis by 2025. Real-time data tracking and analytics.

Analytics 87

Analytics Tools Data Artificial Inteligence 87

O'Reilly Media - Ideas

JANUARY 15, 2019

AI in the enterprise will build upon existing analytic applications. For example, companies are infusing their systems for temporal and geospatial data with deep learning, resulting in scalable and more accurate hybrid systems (i.e., systems that combine deep learning with other machine learning methods).

Trends 84

Trends UI/UX Machine Learning Artificial Inteligence 84

Codegiant

NOVEMBER 9, 2020

Features Scalable API testing tool. Cons The number of requests is limited in the enterprise version. Features Provides visibility on application performance for enterprises. Ability to organize and structure large or enterprise-level software. It helps with building powerful enterprise software applications faster.

Software Review 64

Software Review Tools Weak Development Team Development 64

Codegiant

NOVEMBER 9, 2020

Features Scalable API testing tool. Cons The number of requests is limited in the enterprise version. Features Provides visibility on application performance for enterprises. Ability to organize and structure large or enterprise-level software. It helps with building powerful enterprise software applications faster.

Software Review 52

Software Review Weak Development Team Tools Development 52

Altexsoft

SEPTEMBER 19, 2019

Formatting data according to specified requirements and standards to make it suitable for analysis. The ETL process specifies how a heterogeneous data is retrieved from disparate sources, transformed into a form suitable for the analysis, and loaded into a single destination. Flow of data and ETL. You aim to build custom BI.

Business Intelligence 13

Business Intelligence Tools Data Azure 13