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. Compared to previous CPU-based architectures, CDP 7.1

Enterprise 91

Enterprise Cloud Data Machine Learning 91

Altexsoft

AUGUST 29, 2023

Data lakes emerged as expansive reservoirs where raw data in its most natural state could commingle freely, offering unprecedented flexibility and scalability. This article explains what a data lake is, its architecture, and diverse use cases. Watch our video explaining how data engineering works.

Architecture 52

Architecture Data Storage Machine Learning 52

CIO

NOVEMBER 9, 2022

Given the ongoing gap between the demand for experienced data analysts and the supply of these professionals — and the desire to quickly get valuable business insights into the hands of the users who need it most — it’s easy to see why enterprises would find self-service analytics appealing. That’s a great place to start.”

Analytics 342

Analytics Metrics Government Business Intelligence 342

O'Reilly Media - Ideas

DECEMBER 6, 2018

The O’Reilly Data Show Podcast: Alex Wong on building human-in-the-loop automation solutions for enterprise machine learning. As the use of machine learning and analytics become more widespread, we’re beginning to see tools that enable data scientists and data engineers to scale and tackle many more problems and maintain more systems.

Network 57

Network Architecture Tools Machine Learning 57

Altexsoft

FEBRUARY 11, 2023

This specialist works closely with people on both business and IT sides of a company to understand the current needs of the stakeholders and help them unlock the full potential of data. To get a better understanding of a data architect’s role, let’s clear up what data architecture is. Feel free to enjoy it.

Data 87

Data Data Engineering Big Data Architecture 87

TechCrunch

MAY 18, 2022

Heartex has an office in San Francisco, California, but several of the company’s engineers are based in the former Soviet Republic of Georgia. When asked, Heartex says that it doesn’t collect any customer data and open sources the core of its labeling platform for inspection.

Open Source 203

Open Source Weak Development Team Artificial Inteligence Data 203

CIO

FEBRUARY 13, 2023

Fifty-two percent of organizations plan to increase or maintain their IT spending this year, according to Enterprise Strategy Group. This includes spending on strengthening cybersecurity (35%), improving customer service (32%) and improving data analytics for real-time business intelligence and customer insight (30%).

Budget 363

Budget Artificial Inteligence Technical Review VR 363

Cloudera

OCTOBER 4, 2023

Fast moving data and real time analysis present us with some amazing opportunities. Every organization has some data that happens in real time, whether it is understanding what our users are doing on our websites or watching our systems and equipment as they perform mission critical tasks for us. Don’t blink — or you’ll miss it!

Analytics 88

Analytics Machine Learning Artificial Inteligence Telecommunications 88

RapidValue

JULY 21, 2019

From DevOps to DataOps DataOps can be simply stated as “DevOps for data”. It is a set of practices and technologies that integrate the development and operation of data movement architectures into a continuous process. DataOps aids data practitioners to continuously deliver quality data to applications and business processes.

Business Transformation 65

Business Transformation Enterprise DevOps Analytics 65

Mobilunity

MAY 8, 2023

An Enterprise Data Lake is a large, centralized repository that stores structured and unstructured data at scale. It is designed to store vast amounts of data from a variety of sources. Moreover an Enterprise Data Lake makes it accessible to data scientists, analysts, and other users across the enterprise.

Engineering 52

Engineering Data Storage AWS 52

Agile Engine

SEPTEMBER 29, 2023

Few people know this, but enterprises often employ a machine learning technique that’s instrumental in particle physics experiments at the Large Hadron Collider. In enterprise projects, gradient boosting is typically a part of forecasting, classification, and ranking solutions.

Video 52

Video Machine Learning Artificial Inteligence Automotive 52

Cloudera

JUNE 7, 2022

Cloudera is one of only two visionaries in Gartner’s Cloud DBMS magic quadrant analysis. Also, Cloudera DataFlow is rated highly in the GigaOm Radar for Streaming Data Platforms. Leading industry analysts rated Cloudera better at analytic and operational data use cases than many well-known cloud vendors.

Data 111

Data Architecture Analytics Government 111

Cloudera

FEBRUARY 25, 2021

Today’s enterprise data science teams have one of the most challenging, yet most important roles to play in your business’s ML strategy. However, only 4% of enterprise executives today report seeing success from their ML investment. The implications of ML on the future of business are clear.

Machine Learning 82

Machine Learning Artificial Inteligence Telecommunications Enterprise 82

Cloudera

SEPTEMBER 10, 2021

Key to harnessing the power of all that data: high-powered artificial intelligence tools, machine learning capabilities and applications capable of rapidly exposing attempts at fraud or identity theft. Pairing High-Tech Keys to Unlock the Power of Data.

Artificial Inteligence 68

Artificial Inteligence Machine Learning Artificial Intelligence Engineering 68

Confluent

FEBRUARY 6, 2019

This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers. Impedance mismatch between data scientists, data engineers and production engineers. For now, we’ll focus on Kafka.

Machine Learning 106

Machine Learning Artificial Inteligence Scalability Data Engineering 106

AWS Machine Learning - AI

JANUARY 26, 2024

Understanding and addressing LLM vulnerabilities, threats, and risks during the design and architecture phases helps teams focus on maximizing the economic and productivity benefits generative AI can bring. Many customers are looking for guidance on how to manage security, privacy, and compliance as they develop generative AI applications.

Artificial Inteligence 116

Artificial Inteligence Generative AI Security Applications 116

CIO

APRIL 4, 2023

In one Forrester study and financial analysis, it was found that AI-enabled organizations can gain an ROI of 183% over three years. AI working on top of a data lakehouse, can help to quickly correlate passenger and security data, enabling real-time threat analysis and advanced threat detection. MB every second.

Architecture 130

Architecture Data Analysis Construction 130

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. Hands-on Machine Learning with Python: Clustering, Dimension Reduction, and Time Series Analysis , July 18. Data science and data tools.

Course 65

Course Training Artificial Inteligence Software Review 65

TIBCO - Connected Intelligence

SEPTEMBER 22, 2020

For today’s most mature enterprise cloud architectures, ultra-quick querying capabilities on petabytes of data is what the modern pace of business demands. And for enterprises running AWS, Amazon Redshift is most certainly a part of the data warehousing picture given its size, flexibility, and scale.

AWS 48

AWS Analytics Cloud Analysis 48

Lacework

NOVEMBER 1, 2023

This article addresses privacy in the context of hosting data and considers how privacy by design can be incorporated into the data architecture. In the first article in this series, the topic of privacy by design is covered in some detail, particularly regarding the design of products for enterprise security and data hosting.

System Design 52

System Design Systems Review System Data 52

CIO

DECEMBER 22, 2022

DataOps (data operations) is an agile, process-oriented methodology for developing and delivering analytics. It brings together DevOps teams with data engineers and data scientists to provide the tools, processes, and organizational structures to support the data-focused enterprise. It’s a fluid situation.”

Analytics 325

Analytics Data Engineering Machine Learning Artificial Inteligence 325

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. Hands-on Machine Learning with Python: Clustering, Dimension Reduction, and Time Series Analysis , July 18. Data science and data tools.

Course 49

Course Training Artificial Inteligence Software Review 49

O'Reilly Media - Ideas

MARCH 19, 2020

We use it as a data source for our annual platform analysis , and we’re using it as the basis for this report, where we take a close look at the most-used and most-searched topics in machine learning (ML) and artificial intelligence (AI) on O’Reilly [1]. Among companies using AI to support production use cases, deep learning was No.

Artificial Inteligence 114

Artificial Inteligence Trends Artificial Intelligence Machine Learning 114

O'Reilly Media - Ideas

MAY 1, 2019

Spotlight on Data: Caching Big Data for Machine Learning at Uber with Zhenxiao Luo , June 17. Introduction to Distributed Ledger Technology for Enterprise , July 10. Spotlight on Data: Data as an Asset with Friederike Schüür and Jen van der Meer , May 20. Data science and data tools.

Course 45

Course Training Artificial Inteligence Machine Learning 45

Altexsoft

JUNE 11, 2021

Now, scale it to the enterprise level and just imagine how many processes comprise the daily workflow — and how many optimization opportunities there are IF you could break down and analyze every step of every process. Conformance analysis, source: QPR. What is process mining? Enhancement goes beyond measuring and comparing.

Applications 69

Applications Weak Development Team Systems Review Software Review 69

Cloudera

AUGUST 31, 2021

While this “data tsunami” may pose a new set of challenges, it also opens up opportunities for a wide variety of high value business intelligence (BI) and other analytics use cases that most companies are eager to deploy. . Traditional data warehouse vendors may have maturity in data storage, modeling, and high-performance analysis.

Data 84

Data Analytics Cloud Technical Review 84

UruIT

JUNE 8, 2019

Help enterprises and startups make their systems smarter. Leverage data to create UX-enhancing models . Leverage structured, semi-structured and raw unstructured data. . Discover hidden patterns in data to identify the most relevant insights for the client. Data Collection and Preparation.

Machine Learning 40

Machine Learning Artificial Inteligence Systems Review Software Review 40

Altexsoft

AUGUST 25, 2020

Big data fosters the development of new tools for transporting, storing, and analyzing vast amounts of unstructured data. Prominent enterprises in numerous sectors including sales, marketing, research, and healthcare are actively collecting big data. Data engineering vs big data engineering.

Big Data 75

Big Data Data Engineering Engineering Data 75

TIBCO - Connected Intelligence

OCTOBER 15, 2020

For instance: How will this new capability impact my client’s as-is and future architectures? Towards these trends, our clients have significantly invested in data-related technologies and talent over the past several years, including: Data governance to cater to enterprise-level financial reporting and regulatory compliance as an example.

Virtualization 50

Virtualization Data Energy Innovation 50

Apiumhub

APRIL 1, 2021

It starts with explaining about the digital age, data mining and then moves to explain the kinds of data that can be mined, the patterns that can be mined, for example, cluster analysis, predictive analysis, correlations, etc., Thinking with Data: How to Turn Information into Insights by Max Shron.

Artificial Inteligence 52

Artificial Inteligence Data Handbook Machine Learning 52

Hu's Place - HitachiVantara

JANUARY 3, 2019

In order to utilize the wealth of data that they already have, companies will be looking for solutions that will give comprehensive access to data from many sources. More focus will be on the operational aspects of data rather than the fundamentals of capturing, storing and protecting data.

Trends 86

Trends Artificial Inteligence Data Center Machine Learning 86

Altexsoft

FEBRUARY 8, 2021

Machine learning techniques analyze big data from various sources, identify hidden patterns and unobvious relationships between variables, and create complex models that can be retrained to automatically adapt to changing conditions. Define data sources. Cost control. Quality management.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

Altexsoft

SEPTEMBER 9, 2022

Today, such modern data management frameworks as DataOps strongly rely on effective metadata capture and management to bring order into the chaotic data flows. Plus, a data fabric architecture design approach is also based on metadata as one of the main building blocks. Metadata management components.

Tools 59

Tools Technical Review Software Review Systems Review 59

O'Reilly Media - Ideas

FEBRUARY 11, 2019

The resource examples I’ll cite will be drawn from the upcoming Strata Data conference in San Francisco , where leading companies and speakers will share their learnings on the topics covered in this post. AI and machine learning in the enterprise. AI and machine learning in the enterprise. Foundational data technologies.

Big Data 86

Big Data Technology Tools Cloud 86

Altexsoft

JUNE 25, 2019

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. This discipline is not to be underestimated, as it enables effective data storing and reliable data flow while taking charge of the infrastructure.

Data Engineering 106

Data Engineering Engineering Data Artificial Inteligence 106

Altexsoft

APRIL 13, 2023

Supply chain control tower architecture: main components, integrations, and data sources As we mentioned, an SCCT is typically comprised of multiple components that handle various aspects of supply chain management. Let’s look closer at what’s there under the hood and list the main components, integrations, and data sources.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

Cloudera

DECEMBER 10, 2020

CDW includes two highly scalable and performant Apache open-source engines – Impala and Hive LLAP – that have proven themselves in hundreds of enterprises for business-critical data warehousing. Today, enterprises want data warehouses that support on-demand consumption.

Data 98

Data Technical Review Storage Systems Review 98