Cloudera

OCTOBER 4, 2023

On top of these core critical capabilities, we also need the following: Petabyte and larger scalability — particularly valuable in predictive analytics use cases where high granularity and deep histories are essential to training AI models to greater precision.

Analytics 83

Analytics Machine Learning Artificial Inteligence Telecommunications 83

Apps Associates

JULY 14, 2023

Migrating your Oracle workload to the cloud, specifically Amazon Web Services, can provide numerous benefits for your business. Improved scalability, high availability, enhanced security, cost optimization, and seamless integration with AWS services are just a few advantages worth considering.

Disaster Recovery 52

Disaster Recovery Cloud AWS Backup 52

Apiumhub

FEBRUARY 25, 2021

Machine Learning. Machine learning is the backbone of data science. Using machine learning, predictive analytics and data science, self-driving cars can adjust to speed limits, avoid dangerous lane changes and even take passengers on the quickest route. . Scoring and ranking (e.g., FICO score). Healthcare.

Tools 72

Tools Data Machine Learning Artificial Inteligence 72

RapidValue

APRIL 20, 2020

With faster deployments, scalability and improved visibility across applications, cloud computing is a hit among DevOps-minded teams. Leveraging the automation and scalable features of cloud computing, DevOps teams can drive innovation, achieve agility, resilience and increased business value. The Artificial Intelligence Hype.

DevOps 69

DevOps Trends Artificial Inteligence Serverless 69

Altexsoft

FEBRUARY 11, 2023

What’s more, investing in data products, as well as in AI and machine learning was clearly indicated as a priority. 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.

Data 87

Data Data Engineering Big Data Architecture 87

Apiumhub

MARCH 16, 2021

With more and more data available, it’s getting more difficult to focus on the information we really need and present it in an actionable way and that’s what business intelligence is all about. In this article we will talk about Business Intelligence tools, benefits & use cases. . What is Business Intelligence.

Business Intelligence 118

Business Intelligence Tools Artificial Inteligence Technical Review 118

Gorilla Logic

MAY 19, 2021

Monetize data with technologies such as artificial intelligence (AI), machine learning (ML), blockchain, advanced data analytics , and more. CIO.com notes that it took employers an average of 109 days to fill roles in machine learning and AI, compared to 44 days to fill jobs in general. .

Software Review 94

Software Review Technical Review Software Development Team Review 94

Exadel

FEBRUARY 27, 2023

Whether you opt for supervised machine learning algorithms that feed off structured data or deep learning networks that independently parse large volumes of unstructured information (like images, PDF documents, and social media posts) you need lots of data to train algorithms capable of solving your business problems.

Artificial Inteligence 52

Artificial Inteligence Artificial Intelligence How To Technical Review 52

Altexsoft

FEBRUARY 8, 2021

These challenges can be addressed by intelligent management supported by data analytics and business intelligence (BI) that allow for getting insights from available data and making data-informed decisions to support company development. Comparison between traditional and machine learning approaches to demand forecasting.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

Altexsoft

JUNE 26, 2023

We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. It’s the first and essential stage of data-related activities and projects, including business intelligence , machine learning , and big data analytics. What is data collection?

Machine Learning 52

Machine Learning Artificial Inteligence Data Systems Review 52

Cloudera

AUGUST 30, 2022

Modern data architectures. To eliminate or integrate these silos, the public sector needs to adopt robust data management solutions that support modern data architectures (MDAs). Data Mesh: A type of data platform architecture that embraces the ubiquity of data in the enterprise by leveraging a domain-oriented, self-serve design.

Architecture 75

Architecture Data Artificial Inteligence Artificial Intelligence 75

Cloudera

DECEMBER 10, 2020

Recently, cloud-native data warehouses changed the data warehousing and business intelligence landscape. Appealing directly to end-users in the Lines of Business (LOBs), these solutions can dramatically shorten time to value, lower administrative burdens, and promise continuous agility in response to changing business demands.

Data 98

Data Technical Review Storage Systems Review 98

Infinidat

MARCH 10, 2021

Re-Thinking the Storage Infrastructure for Business Intelligence. When paired with the accelerated compute so often deployed with AI/ML-driven workloads, traditional storage architectures are severely challenged to keep the processors fed with data and operating efficiently – let alone meeting response time requirements.

Business Intelligence 98

Business Intelligence Storage Infrastructure Artificial Inteligence 98

CTOvision

JULY 9, 2014

The data is too big, moves too fast, or does not fit the structures of your database architectures. However, massively parallel processing (MPP) database architectures are one example of purpose-built technologies that have been developed to support both OLTP and OLAP data structures at enormous scales up into the petabytes (PB).

Big Data 114

Big Data Data CTO Fractional CTO 114

CIO

MARCH 2, 2023

“In general, it’s been straight forward to quantify the business impact of automation initiatives, given they typically have clear before and after business metrics. It has the potential to improve business KPIs through auto-detect, auto-heal solutions, and create new channels to improve end-user experience,” he says.

Artificial Inteligence 358

Artificial Inteligence Pharmaceuticals Analytics Artificial Intelligence 358

CIO

MARCH 9, 2022

Newer data lakes are highly scalable and can ingest structured and semi-structured data along with unstructured data like text, images, video, and audio. They conveniently store data in a flat architecture that can be queried in aggregate and offer the speed and lower cost required for big data analytics.

Artificial Inteligence 298

Artificial Inteligence Data Artificial Intelligence Analytics 298

Altexsoft

NOVEMBER 10, 2021

A data lakehouse , as the name suggests, is a new data architecture that merges data warehouse and data lake into a single whole, aiming at addressing each one’s limitations. Traditional data warehouse platform architecture. Data lake architecture example. What is a data lakehouse?

Architecture 52

Architecture Data Storage Machine Learning 52

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. to develop all the data architecture and analytics solutions. Scalability.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

Altexsoft

APRIL 23, 2019

The answer is business intelligence. We’ve already discussed a machine learning strategy. In this article, we will discuss the actual steps of bringing business intelligence into your existing corporate infrastructure. What is business intelligence? Source: Skydesk.jp. Reporting (BI) tools.

Business Intelligence 93

Business Intelligence Analytics Tools Strategy 93

Altexsoft

SEPTEMBER 9, 2022

Plus, a data fabric architecture design approach is also based on metadata as one of the main building blocks. You can get more information about data labeling in machine learning from another post (it’s one of the main steps of preparing datasets for ML). Ensure its scalability and integrability.

Tools 59

Tools Technical Review Software Review Systems Review 59

Altexsoft

JANUARY 22, 2020

A complete guide to business intelligence and analytics. The role of business intelligence developer. When we talk about traditional analytics, we mean business intelligence (BI) methods and technical infrastructure. BI is a practice of supporting data-driven business decision-making.

Analytics 20

Analytics Data IoT Analysis 20

Altexsoft

SEPTEMBER 23, 2021

This article explains the main concepts of a data hub, its architecture, and how it differs from data warehouses and data lakes. It’s not a single technology, but rather an architectural approach that unites storages, data integration and orchestration tools. What is Data Hub?

Architecture 52

Architecture Data Storage IoT 52

Cloudera

JUNE 30, 2022

Today’s general availability announcement covers Iceberg running within key data services in the Cloudera Data Platform (CDP) — including Cloudera Data Warehousing ( CDW ), Cloudera Data Engineering ( CDE ), and Cloudera Machine Learning ( CML ). But the current data lakehouse architectural pattern is not enough.

Data 83

Data Analytics Machine Learning Artificial Inteligence 83

Datavail

JUNE 8, 2023

From the technical possibilities and challenges of new and emerging technologies to using Big Data for business intelligence, analytics, and other business strategies, this event had something for everyone. I’ll recap our presentations and everything else the Datavail team learned at Data Summit 2023.

Database Administration 52

Database Administration Data Artificial Inteligence Analytics 52

Altexsoft

APRIL 26, 2022

Not long ago setting up a data warehouse — a central information repository enabling business intelligence and analytics — meant purchasing expensive, purpose-built hardware appliances and running a local data center. This demand gave birth to cloud data warehouses that offer flexibility, scalability, and high performance.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

Altexsoft

JULY 18, 2023

This article will expose Apache Spark architecture, assess its advantages and disadvantages, compare it with other big data technologies, and provide you with the path to learning this impactful instrument. Machine learning. For this, we have a short, engaging video. How data engineering works in a nutshell.

Weak Development Team 52

Weak Development Team Big Data Data Machine Learning 52

Coforge

AUGUST 2, 2019

This was actually the scenario across the enterprise and hence an urgent need arose to build an agile infrastructure that could deliver computing and solutions to the business and create new software products and services for our customers. Regulations: is another critical factor.

Cloud 8

Cloud Infrastructure Agile Architecture 8

Altexsoft

JANUARY 14, 2021

We’ll review all the important aspects of their architecture, deployment, and performance so you can make an informed decision. Thanks to the capability of data warehouses to get all data in one place, they serve as a valuable business intelligence (BI) tool, helping companies gain business insights and map out future strategies.

Backup 115

Backup Azure Software Review Systems Review 115

Altexsoft

OCTOBER 24, 2019

The focus of this material is to provide information about the business value of each architectural and conceptual approach to building a warehouse. Such practice is a futureproof way of storing data for business intelligence (BI) , which is a set of methods/technologies of transforming raw data into actionable insights.

Architecture 50

Architecture Enterprise Data Technical Review 50

Altexsoft

MAY 20, 2020

IoT architecture layers. IoT infrastructure contains several key layers, with an IoT platform acting as a bridge between physical world and business processes. Amazon claims that the module is scalable enough to handle over a billion devices, with each of them getting assigned a unique identity. It easily integrates with.

IoT 141

IoT Azure AWS Transportation 141

Altexsoft

MARCH 18, 2021

From the late 1980s, when data warehouses came into view, and up to the mid-2000s, ETL was the main method used in creating data warehouses to support business intelligence (BI). Cloud data warehouses such as Snowflake, Redshift, and BigQuery also support ELT, as they separate storage and compute resources and are highly scalable.

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

Altexsoft

SEPTEMBER 21, 2023

In 2023, Elasticsearch introduced the Elasticsearch Relevance Engine (ESRE) , a powerful upgrade integrating AI and machine learning into search. Elasticsearch supports machine learning algorithms that can automatically model and analyze the behavior of your data in real time, providing valuable insights and predictions.

Weak Development Team 52

Weak Development Team Analytics Engineering Development Team Review 52

Kentik

FEBRUARY 14, 2023

With software architectures increasingly adopting distributed, cloud-based models , network infrastructures have become complex webs of virtual and physical devices. Business intelligence with data platforms The context of this data innovation is simple: driving business goals forward and delighting customers.

Network 52

Network Data Artificial Inteligence Analysis 52

Existek

JANUARY 27, 2023

For example, many financial institutions are now using artificial intelligence and machine learning to analyze customer data and identify new opportunities for growth. Scalability is also a significant challenge for financial services software development.

Software Development 52

Software Development Trends Technology Software 52

Cloudera

NOVEMBER 2, 2020

Data streamed in is queryable in conjunction with historical data, avoiding need for Lambda Architecture. Figure 1 below shows a standard architecture for a Real-Time Data Warehouse. Basic Architecture for Real-Time Data Warehousing. for active archive or joining live data with historical data), or machine learning.

Data 90

Data Analytics Storage Big Data 90

Altexsoft

DECEMBER 14, 2022

The heart and soul of Docker are containers — lightweight virtual software packages that combine application source code with all the dependencies such as system libraries (libs) and binary files as well as external packages, frameworks, machine learning models, and more. Docker architecture core components. Docker Architecture.

Weak Development Team 52

Weak Development Team Linux Operating System Virtualization 52

Altexsoft

JULY 29, 2022

According to the study by the Business Application Research Center (BARC), Hadoop found intensive use as. a suitable technology to implement data lake architecture. Apache Hadoop architecture. In other words, it shares no resources with other machines except for a common network. How YARN master-slave architecture works.

Big Data 59

Big Data Data Google Cloud Storage 59