Data Virtualization

JANUARY 19, 2023

The post Modernizing Data Analytics Architecture with the Denodo Platform on Azure appeared first on Data Virtualization blog - Data Integration and Modern Data Management Articles, Analysis and Information. Unfortunately, with data spread.

Azure 52

Azure Architecture Analytics Data 52

Cloudera

JUNE 18, 2022

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

Data 91

Data Analytics Open Source Architecture 91

Apps Associates

JULY 14, 2023

Outcome highlights: Cost consolidation / reduction, business continuity, improved future state architecture with ability to leverage breadth of AWS services Pearson plc is the world’s learning company with more than 22,500 employees operating in 70 countries.

Disaster Recovery 52

Disaster Recovery Cloud AWS Backup 52

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. To get a better understanding of a data architect’s role, let’s clear up what data architecture is. machine learning and deep learning models; and business intelligence tools.

Data 87

Data Data Engineering Big Data Architecture 87

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

Trigent

JUNE 20, 2022

For example, McDonald’s collaborated with data engineering firms to automate verbal order intake via machine learning and natural language processing (NLP). The business need was to shorten wait times, improve order accuracy and free up restaurant employees to focus on enhancing one-to-one service.

Data Engineering 52

Data Engineering Engineering Data Strategy 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

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

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 82

Data Analytics Cloud Technical Review 82

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. Set up data storage technology.

Machine Learning 52

Machine Learning Artificial Inteligence Data Systems Review 52

Altexsoft

MAY 6, 2022

When ice cream melts in your hands on a hot day, it can be a bit frustrating; but if a load of vaccines can’t be used because it went bad due to wrong storage or transportation conditions, the results are a lot more serious, if not fatal. So, it’s important that all the parties of supply chains (3PLs, carriers, storage facilities, etc.)

Transportation 52

Transportation How To Pharmaceuticals Storage 52

Infinidat

MARCH 10, 2021

Re-Thinking the Storage Infrastructure for Business Intelligence. 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. Adriana Andronescu. Wed, 03/10/2021 - 12:42.

Business Intelligence 98

Business Intelligence Storage Infrastructure Artificial Inteligence 98

Altexsoft

SEPTEMBER 9, 2022

Metadata management is a set of activities, technologies, and policies that target metadata collection, storage, and organizing. Plus, a data fabric architecture design approach is also based on metadata as one of the main building blocks. Metadata storage usually implies developing a specialized repository. Metadata storage.

Tools 59

Tools Technical Review Software Review Systems Review 59

CIO

MARCH 9, 2022

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. This dual-system architecture requires continuous engineering to ETL data between the two platforms. On the other hand, they don’t support transactions or enforce data quality.

Artificial Inteligence 279

Artificial Inteligence Data Artificial Intelligence Analytics 279

CTOvision

JULY 9, 2014

In the text below, I examine an on-premise Hadoop ecosystem as a general purpose Big Data solution in relation to alternative commercial purpose-built storage technologies (-e.g. The data is too big, moves too fast, or does not fit the structures of your database architectures. Oracle, Teradata, IBM, SAP, Microsoft, EMC, etc).

Big Data 114

Big Data Data CTO Fractional CTO 114

Cloudera

AUGUST 30, 2022

Agencies are plagued by a wide range of data formats and storage environments—legacy systems, databases, on-premises applications, citizen access portals, innumerable sensors and devices, and more—that all contribute to a siloed ecosystem and the data management challenge. . Modern data architectures. Forrester ).

Architecture 77

Architecture Data Artificial Inteligence Artificial Intelligence 77

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. In a nutshell, the lakehouse system leverages low-cost storage to keep large volumes of data in its raw formats just like data lakes. 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.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

Altexsoft

AUGUST 12, 2020

This article describes IoT through its architecture, layer to layer. Before we go any further, it’s worth pointing out that there is no single, agreed-upon IoT architecture. It varies in complexity and number of architectural layers depending on a particular business task. analytic solutions using machine learning.

IoT 140

IoT Architecture Wireless Transportation 140

Altexsoft

APRIL 22, 2020

The data can be further applied to provide value for machine learning , data stream analysis , business intelligence , or any other type of analytics. To give you an idea of what a data platform can be, and which tools are used to process data, let’s quickly outline some general architectural principles.

Data Engineering 69

Data Engineering Engineering Artificial Inteligence Data 69

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

OCTOBER 30, 2021

As the complexity of tasks and the volume of data needed to process increased, data scientists started focusing more on helping businesses solve problems. Data scientists today are business-oriented analysts who know how to shape data into answers, often building complex machine learning models. Choosing an algorithm.

Data Engineering 98

Data Engineering Engineering Data Machine Learning 98

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

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

Altexsoft

SEPTEMBER 23, 2021

Evidently, common storage solutions fail to provide a unified data view and meet the needs of companies for seamless data flow. This article explains the main concepts of a data hub, its architecture, and how it differs from data warehouses and data lakes. A data warehouse (DW) is a unified storage for all corporate data.

Architecture 52

Architecture Data Storage IoT 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. The platform provides fast, flexible, and easy-to-use options for data storage, processing, and analysis.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

Altexsoft

OCTOBER 24, 2019

While our brain is both the processor and the storage, companies need multiple tools to work with data. The focus of this material is to provide information about the business value of each architectural and conceptual approach to building a warehouse. Similar to humans companies generate and collect tons of data about the past.

Architecture 50

Architecture Enterprise Data Technical Review 50

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 85

Data Analytics Machine Learning Artificial Inteligence 85

Coforge

AUGUST 2, 2019

As Technology Operations Manager of the Securities Sales & Trading business unit of a global investment bank, I was forced to ponder over how agile we were in responding to the needs of the business. The investments on infrastructure had reached levels where additional demands for storage and computing were leading to confrontations.

Cloud 8

Cloud Infrastructure Agile Architecture 8

Altexsoft

JANUARY 14, 2021

From simple mechanisms for holding data like punch cards and paper tapes to real-time data processing systems like Hadoop, data storage systems have come a long way to become what they are now. For over 30 years, data warehouses have been a rich business-insights source. Data warehouse architecture. Is it still so?

Backup 115

Backup Azure Software Review Systems Review 115

Altexsoft

MARCH 31, 2020

And, as is common, to transform it before loading to another storage system. A data pipeline is a set of tools and activities for moving data from one system, with its method of data storage and processing, to another system in which it can be stored and managed differently. We’ll get back to the types of storages a bit later.

Data 76

Data Storage Analytics Data Center 76

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. These hardware components cache and preprocess real-time data, reducing the burden on central storages and main processors. Transport layer: networks and gateways.

IoT 141

IoT Azure AWS Transportation 141

Cloudera

JANUARY 21, 2021

With CDW, as an integrated service of CDP, your line of business gets immediate resources needed for faster application launches and expedited data access, all while protecting the company’s multi-year investment in centralized data management, security, and governance. Architecture overview. Separate storage.

Analytics 93

Analytics Storage Technical Review Virtualization 93

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

Kentik

FEBRUARY 14, 2023

With software architectures increasingly adopting distributed, cloud-based models , network infrastructures have become complex webs of virtual and physical devices. With storage metadata, data platforms offer engineers opportunities for additional insights into data access, resource allotment and capacity, performance, and more.

Network 52

Network Data Artificial Inteligence Analysis 52

Altexsoft

JULY 29, 2022

Apache Hadoop is an open-source Java-based framework that relies on parallel processing and distributed storage for analyzing massive datasets. According to the study by the Business Application Research Center (BARC), Hadoop found intensive use as. a suitable technology to implement data lake architecture. What is Hadoop?

Big Data 59

Big Data Data Google Cloud Storage 59

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