AWS Machine Learning - AI

JANUARY 26, 2024

Generative artificial intelligence (AI) applications built around large language models (LLMs) have demonstrated the potential to create and accelerate economic value for businesses. We then discuss how building on a secure foundation is essential for generative AI.

Artificial Inteligence 131

Artificial Inteligence Generative AI Security Applications 131

CIO

FEBRUARY 14, 2023

By George Trujillo, Principal Data Strategist, DataStax Increased operational efficiencies at airports. Investments in artificial intelligence are helping businesses to reduce costs, better serve customers, and gain competitive advantage in rapidly evolving markets. Instant reactions to fraudulent activities at banks.

Artificial Inteligence 284

Artificial Inteligence Strategy Data Machine Learning 284

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.

Artificial Inteligence 107

Artificial Inteligence Machine Learning Scalability Data Engineering 107

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

Data analytics is a discipline focused on extracting insights from data. It comprises the processes, tools and techniques of data analysis and management, including the collection, organization, and storage of data. In business, predictive analytics uses machine learning, business rules, and algorithms.

Analytics 337

Analytics Data Analysis Business Analytics 337

Altexsoft

MAY 27, 2020

Machine learning (ML) history can be traced back to the 1950s, when the first neural networks and ML algorithms appeared. Analysis of more than 16.000 papers on data science by MIT technologies shows the exponential growth of machine learning during the last 20 years pumped by big data and deep learning advancements.

Artificial Inteligence 89

Artificial Inteligence Machine Learning Architecture Training 89

Cloudera

JANUARY 20, 2021

Machine learning is now being used to solve many real-time problems. One big use case is with sensor data. Corporations now use this type of data to notify consumers and employees in real-time. Serving The Model . Make sure you read Part 1 and Part 2 before reading this installment. Background / Overview.

Artificial Inteligence 116

Artificial Inteligence Machine Learning Applications Data 116

Cloudera

AUGUST 22, 2024

The Indian Talent Prowess Over nearly a decade, the Bangalore CoE has grown into a robust hub, housing over 600 employees, primarily in engineering roles, which form the backbone of product innovation and customer support together with the team in Chennai.

Innovation 71

Innovation Artificial Inteligence Machine Learning Technical Review 71

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

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

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

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 Artificial Inteligence Machine Learning Weak Development Team 90

Mobilunity

MAY 8, 2023

Key zones of an Enterprise Data Lake Architecture typically include ingestion zone, storage zone, processing zone, analytics zone, and governance zone. Ingestion zone is where data is collected from various sources and ingested into the data lake. Storage zone is where the raw data is stored in its original format.

Engineering 52

Engineering Data Storage AWS 52

Altexsoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data.

Architecture 52

Architecture Data Storage Machine Learning 52

Cloudera

JANUARY 20, 2021

The missing chapter is not about point solutions or the maturity journey of use cases, the missing chapter is about the data, it’s always been about the data, and most importantly the journey data weaves from edge to artificial intelligence insight. . STEP 3: Monitor data throughput from each factory.

Data 114

Data Artificial Inteligence Analytics Machine Learning 114

AWS Machine Learning - AI

AUGUST 8, 2024

As one of the largest AWS customers, Twilio engages with data, artificial intelligence (AI), and machine learning (ML) services to run their daily workloads. Data is the foundational layer for all generative AI and ML applications. The following diagram illustrates the solution architecture.

Artificial Inteligence 105

Artificial Inteligence Data Generative AI AWS 105

Altexsoft

AUGUST 25, 2020

Big data can be quite a confusing concept to grasp. What to consider big data and what is not so big data? Big data is still data, of course. But it requires a different engineering approach and not just because of its amount. Data engineering vs big data engineering.

Big Data 75

Big Data Data Engineering Engineering Data 75

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. More formats, more engines, more interoperability.

Data 97

Data Analytics Open Source Architecture 97

Hu's Place - HitachiVantara

NOVEMBER 11, 2018

Hybrid clouds must bond together the two clouds through fundamental technology, which will enable the transfer of data and applications. REAN Cloud is a global cloud systems integrator, managed services provider and solutions developer of cloud-native applications across big data, machine learning and emerging internet of things (IoT) spaces.

Cloud 78

Cloud Google Cloud Azure AWS 78

Altexsoft

APRIL 22, 2020

So, along with data scientists who create algorithms, there are data engineers, the architects of data platforms. In this article we’ll explain what a data engineer is, the field of their responsibilities, skill sets, and general role description. What is a data engineer?

Data Engineering 69

Data Engineering Engineering Artificial Inteligence Data 69

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. All you have to do is to alter the table properties to set the storage handler to “HiveIcebergStorageHandler.”

Backup 74

Backup Data Engineering Engineering Data 74

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 Artificial Inteligence 98

Altexsoft

JUNE 14, 2021

Lemonade uses Natural Action Synthesis and Natural Language Processing to ensure that Maya gets smarter the more it chats. This is possible because their machine learning model is retrained almost daily. Your vision on personalization may not work for every business model. Personalization isn’t a one-time project.

Insurance 88

Insurance Machine Learning Artificial Inteligence Policies 88

O'Reilly Media - Ideas

APRIL 9, 2019

A few months ago, I wrote about the differences between data engineers and data scientists. An interesting thing happened: the data scientists started pushing back, arguing that they are, in fact, as skilled as data engineers at data engineering. I agree; learn as much as you can.

Data Engineering 111

Data Engineering Engineering Data Technical Review 111

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 86

Data Analytics Cloud Technical Review 86

Altexsoft

JULY 18, 2023

On the other hand, the term spark often brings to mind a tiny particle that, despite its size, can start a large fire. These seemingly unrelated terms unite within the sphere of big data, representing a processing engine that is both enduring and powerfully effective — Apache Spark. Big data processing.

Weak Development Team 52

Weak Development Team Big Data Data Machine Learning 52

Altexsoft

JUNE 25, 2019

Being at the top of data science capabilities, machine learning and artificial intelligence are buzzing technologies many organizations are eager to adopt. 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.

Data Engineering 106

Data Engineering Engineering Data Artificial Inteligence 106

Cloudera

MAY 22, 2018

With CDSW, organizations can research and experiment faster, deploy models easily and with confidence, as well as rely on the wider Cloudera platform to reduce the risks and costs of data science projects. for the Oracle Big Data Appliance). The post Now Available: Cloudera Data Science Workbench Release 1.4

Data 42

Data Load Balancer Machine Learning Artificial Inteligence 42

Altexsoft

JUNE 26, 2023

While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection?

Artificial Inteligence 52

Artificial Inteligence Machine Learning Data Systems Review 52

ParkMyCloud

JULY 30, 2019

The Databricks platform allows enterprises to build their data pipelines across data storage systems and prepare data sets for data scientists and engineers. To do this, Databricks offers a range of tools for building, managing and monitoring data pipelines.

Azure 40

Azure AWS Analytics Machine Learning 40

AWS Machine Learning - AI

SEPTEMBER 3, 2024

Harnessing the power of big data has become increasingly critical for businesses looking to gain a competitive edge. From deriving insights to powering generative artificial intelligence (AI) -driven applications, the ability to efficiently process and analyze large datasets is a vital capability.

Serverless 98

Serverless AWS Artificial Inteligence Big Data 98

Existek

JANUARY 11, 2022

In 2010, they launched Windows Azure, the PaaS, positioning it as an alternative to Google App Engine and Amazon EC2. They provided a few services like computing, Azure Bob storage, SQL Azure, and Azure Service Bus. The new structure enabled the opportunity to meet such customer needs in computing as storage, networking, and services.

Azure 52

Azure AWS Cloud How To 52

Altexsoft

APRIL 13, 2023

“Control towers are the artificial intelligence (AI) of supply chain. You can read the details on them in the linked articles, but in short, data warehouses are mostly used to store structured data and enable business intelligence , while data lakes support all types of data and fuel big data analytics and machine learning.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

Altexsoft

JULY 29, 2022

Depending on how you measure it, the answer will be 11 million newspaper pages or… just one Hadoop cluster and one tech specialist who can move 4 terabytes of textual data to a new location in 24 hours. Developed in 2006 by Doug Cutting and Mike Cafarella to run the web crawler Apache Nutch, it has become a standard for Big Data analytics.

Big Data 59

Big Data Data Google Cloud Open Source 59

Altexsoft

SEPTEMBER 9, 2022

In data science , metadata is one of the central aspects: It describes data (including unstructured data streams) fed into a big data analytical platform, capturing, for example, formats, file sizes, source of information, permission details, etc. Metadata storage. Types of metadata.

Tools 59

Tools Technical Review Software Review Systems Review 59

Altexsoft

JUNE 7, 2021

Hadoop and Spark are the two most popular platforms for Big Data processing. They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. Which Big Data tasks does Spark solve most effectively? How does it work?

Big Data 98

Big Data Tools Data Storage 98

Altexsoft

MAY 14, 2021

Big Data enjoys the hype around it and for a reason. But the understanding of the essence of Big Data and ways to analyze it is still blurred. This post will draw a full picture of what Big Data analytics is and how it works. Big Data and its main characteristics. Key Big Data characteristics.

Big Data 78

Big Data Analytics Tools Applications 78