Altexsoft

FEBRUARY 8, 2021

diversity of sales channels, complex structure resulting in siloed data and lack of visibility. 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.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

Altexsoft

MAY 20, 2020

For the most part, they belong to the Internet of Things (IoT), or gadgets capable of communicating and sharing data without human interaction. The number of active IoT connections is expected to double by 2025, jumping from the current 9.9 Source: IoT Analytics. IoT architecture layers. billion to 21.5

IoT 141

IoT Azure AWS Transportation 141

Altexsoft

JANUARY 22, 2020

Similar to a real world stream of water, continuous transition of data received the name streaming , and now it exists in different forms. Media streaming is one of them, but it’s only a visible part of an iceberg where data streaming is used. As a result, it became possible to provide real-time analytics by processing streamed data.

Analytics 20

Analytics Data IoT Analysis 20

Altexsoft

JULY 18, 2023

These seemingly unrelated terms unite within the sphere of big data, representing a processing engine that is both enduring and powerfully effective — Apache Spark. Maintained by the Apache Software Foundation, Apache Spark is an open-source, unified engine designed for large-scale data analytics. Big data processing.

Weak Development Team 52

Weak Development Team Big Data Data Machine Learning 52

Altexsoft

APRIL 13, 2023

Due to extensive usage of connected IoT devices and advanced processing technologies, SCCTs not only gather data and build operational reports but also create predictions, define the impact of various macro- and microeconomic factors on the supply chain, and run “what-if” scenarios to find the best course of action.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

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

Altexsoft

NOVEMBER 10, 2021

The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. What is a data lakehouse? Traditional data warehouse platform architecture. Data lake architecture example.

Architecture 52

Architecture Data Storage Machine Learning 52

Altexsoft

SEPTEMBER 23, 2021

One of the innovative ways to address this problem is to build a data hub — a platform that unites all your information sources under a single umbrella. This article explains the main concepts of a data hub, its architecture, and how it differs from data warehouses and data lakes. What is Data Hub?

Architecture 52

Architecture Data Storage IoT 52

Altexsoft

OCTOBER 24, 2019

We will define how enterprise warehouses are different from the usual ones, what types of data warehouses exist, and how they work. The focus of this material is to provide information about the business value of each architectural and conceptual approach to building a warehouse. What is an Enterprise Data Warehouse?

Architecture 50

Architecture Enterprise Data Technical Review 50

Altexsoft

OCTOBER 21, 2022

Apache Kafka is an open-source, distributed streaming platform for messaging, storing, processing, and integrating large data volumes in real time. It offers high throughput, low latency, and scalability that meets the requirements of Big Data. Kafka architecture. Kafka cluster architecture. Scalability.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Open Source 93

Altexsoft

FEBRUARY 22, 2022

Such an approach requires a great deal of investment since a whole ecosystem has to be created, including IoT sensors installation, acquiring specialized software, creating and maintaining machine learning (ML) models, engaging IT and data science specialists , and so on. Collecting data from connected sensors and external sources.

Software Review 52

Software Review Technical Review Software Technology 52

Hu's Place - HitachiVantara

FEBRUARY 15, 2019

In the case of Hybrid and multi-cloud, we are mixing up multiple clouds which increases operational and data management complexity. Operational policies and methods are different and aggregation of data across multiple clouds boundaries makes it difficult for governance, analytics, and business intelligence.

Cloud 49

Cloud AWS Open Source Data Center 49

Altexsoft

JUNE 26, 2023

Data collection is a methodical practice aimed at acquiring meaningful information to build a consistent and complete dataset for a specific business purpose — such as decision-making, answering research questions, or strategic planning. Structured data is modeled to be easily searchable and occupy minimal storage space.

Machine Learning 52

Machine Learning Artificial Inteligence Data Systems Review 52

CTOvision

JUNE 22, 2015

The HANA platform has completely changed the database industry by combining database, data processing, and application platform capabilities into a single in-memory platform. With this capability, organizations are changing the way they analyze their data. New IBM-SAP Sales-Kit for Business Partner available (ibm.com).

Sport 116

Sport Comparison Internet Games 116

Altexsoft

FEBRUARY 24, 2023

To start with it, you have to be closely familiar with microservices-based architecture, containers, networking, cloud-native technologies, continuous delivery and integration practices, infrastructure as code , and more. Let’s see what common challenges organizations face when using the technology.

Weak Development Team 83

Weak Development Team Load Balancer Technical Review Microservices 83

Altexsoft

OCTOBER 2, 2020

Key disciplines and roles in data management. Data architecture: aligning technologies with business goals. Specialist responsible for the area: data architect. Data architecture is a starting point for any data management model. Snowflake data management processes.

Strategy 64

Strategy Database Administration Data Technical Review 64

Altexsoft

JUNE 20, 2019

This is one of the best use cases for MySQL database, as OLAP/OLTP don’t require complex queries and large volumes of data. Also, consider applying MySQL for the same reason if you’re building a business intelligence tool. Oracle’s multi-model solution allows for accommodating and processing a vast amount of data.

Systems Review 85

Systems Review System Software Review Open Source 85

O'Reilly Media - Ideas

SEPTEMBER 11, 2019

Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena.

Conference 8

Conference Data Data Engineering Big Data 8

CIO

JANUARY 20, 2023

2] Foundational considerations include compute power, memory architecture as well as data processing, storage, and security. It’s About the Data For companies that have succeeded in an AI and analytics deployment, data availability is a key performance indicator, according to a Harvard Business Review report. [3]

Analytics 342

Analytics Artificial Inteligence Artificial Intelligence Hardware 342

Altexsoft

OCTOBER 17, 2019

Low-quality data can also impede and slow down the integration of business intelligence and ML-powered predictive analytics. US company executives that participated in the Data trust pulse survey by PricewaterhouseCoopers noted that unreliable data is one of the obstacles to monetizing data. Data linking .

Tools 16

Tools Data Technical Advisors Technical Review 16

Altexsoft

DECEMBER 9, 2020

Diagnostic analytics identifies patterns and dependencies in available data, explaining why something happened. Predictive analytics creates probable forecasts of what will happen in the future, using machine learning techniques to operate big data volumes. Data warehouse architecture. Analytics maturity model.

Analytics 102

Analytics Technical Review Technology Applications 102

Agile Engine

DECEMBER 27, 2023

From emerging trends to hiring a data consultancy, this article has everything you need to navigate the data analytics landscape in 2024. What is a data analytics consultancy? Big data consulting services 5. 4 types of data analysis 6. Data analytics use cases by industry 7. Table of contents 1.

Big Data 52

Big Data Analytics Data Analysis 52

Altexsoft

MARCH 14, 2023

Known as the Modern Data Stack (MDS) , this suite of tools and technologies has transformed how businesses approach data management and analysis. What is a modern data stack? A data stack, in turn, focuses on data : It helps businesses manage data and make the most out of it.

Data 59

Data Technical Review Software Review Open Source 59

Datavail

SEPTEMBER 8, 2022

Big data presents challenges in terms of volume, velocity, and variety—but that doesn’t mean you have to suffer from a bloated IT ecosystem to address these challenges. In fact, many businesses can realize significant advantages from streamlining their data integration pipelines, trimming away unnecessary tools and services.

Data 40

Data Nonprofit Quality Assurance Education 40