Altexsoft

JANUARY 22, 2020

With the uprise of internet-of-things (IoT) devices, overall data volume increase, and engineering advancements in this field led to new ways of collecting, processing, and analysing data. As a result, it became possible to provide real-time analytics by processing streamed data.

Analytics 20

Analytics Data IoT Analysis 20

Xebia

JANUARY 19, 2023

. – AltexSoft All the data processing is done in Big Data frameworks like MapReduce, Spark and Flink. – Jesse Anderson The data engineering field could be thought of as a superset of business intelligence and data warehousing that brings more elements from software engineering.

Data Engineering 130

Data Engineering Engineering Data Technical Review 130

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. Optimization opportunities offered by analytics.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

Cloudera

MAY 15, 2019

He is a successful architect of healthcare data warehouses, clinical and business intelligence tools, big data ecosystems, and a health information exchange. The Enterprise Data Cloud – A Healthcare Perspective. The analytics and data platform is powering different data needs, use cases, and growth.

Enterprise 47

Enterprise Cloud Data Healthcare 47

Altexsoft

JUNE 14, 2021

On top of that, the company uses big data analytics to quantify losses and predict risks by placing the client into a risk group and quoting a relevant premium. The groups are created using algorithms that collect extensive customer data, such as health conditions. You’ll need a data engineering team for that.

Insurance 88

Insurance Machine Learning Artificial Inteligence Policies 88

N2Growth Blog

JANUARY 23, 2018

Businesses must also take advantage of customer telemetry, Big Data, generated by activity on websites, mobile devices, and social media, to create a more personalized experience — both in-house and online. But not every business knows how to convert that data into actionable insights.

Innovation 84

Innovation Strategy Big Data Advertising 84

Cloudera

SEPTEMBER 12, 2018

It’s a big week for us, as many Clouderans descend on New York for the Strata Data Conference. The week is typically filled with exciting announcements from Cloudera and many partners and others in the data management, machine learning and analytics industry. Technical Impact. Enterprise Machine Learning: .

Artificial Inteligence 45

Artificial Inteligence Data Machine Learning Pharmaceuticals 45

Kentik

MARCH 7, 2018

IoT plays a key role in sensing all of the critical elements in the physical world and delivering a continuous feed of sensor data to a Big Data analytics cluster situated in the cloud. McKinsey offers a typical definition: “We define Industry 4.0 Industry 4.0 Industry 4.0 An Industry 4.0

Industry 40

Industry Data Center WAN Big Data 40

Altexsoft

APRIL 13, 2023

The annual IHS Markit Supply Chain Survey Report found that 63 percent of companies don’t have sufficient technology to approach their top priority optimization strategy, i.e., spend analytics (the situation within other strategic areas is similar). It also often includes analytics, reporting, and forecasting capabilities.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

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

TIBCO - Connected Intelligence

JUNE 9, 2020

The traditional technology approach to logistics has been to host everything in a data warehouse and use extract, transform, and load (ETL) tools to rationalize data followed by a series of business intelligence tools to analyze it. Click To Tweet.

Technology 32

Technology Big Data Blockchain Innovation 32

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.

Big Data 78

Big Data Analytics Tools Applications 78

Openxcell

JANUARY 6, 2023

Instead of making substantial investments in databases, software, and hardware, businesses prefer to access their computing power over the internet or in the cloud. Just a few of the existing cloud services include servers, storage, databases, networking, software, analytics, and business intelligence.

Architecture 52

Architecture Cloud Storage Google Cloud 52

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

TechCrunch

JUNE 25, 2021

He acknowledges that traditional big data warehousing works quite well for business intelligence and analytics use cases. But that’s not real-time and also involves moving a lot of data from where it’s generated to a centralized warehouse. That whole model is breaking down.”

Machine Learning 210

Machine Learning Artificial Inteligence Big Data Business Intelligence 210

ParkMyCloud

MAY 29, 2019

Business Intelligence Analyst. A BI analyst has strong skills in database technology, analytics, and reporting tools and excellent knowledge and understanding of computer science, information systems or engineering. BI Analyst can also be described as BI Developers, BI Managers, and Big Data Engineer or Data Scientist.

Trends 72

Trends Cloud IoT Artificial Inteligence 72

Altexsoft

DECEMBER 23, 2022

Whether your goal is data analytics or machine learning , success relies on what data pipelines you build and how you do it. But even for experienced data engineers, designing a new data pipeline is a unique journey each time. Data engineering in 14 minutes. Data availability. Order of process phases.

Tools 52

Tools Software Review Systems Review Testing 52

Altexsoft

MARCH 24, 2021

They enable interoperability or smooth data exchange between health systems and create fertile ground for telehealth app development as they. applying business intelligence tools to draw insights from data. FHIR Store API to manage clinical data in a FHIR database. This include. What can you build with the API?

Tools 69

Tools Healthcare Insurance Video 69

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

Altexsoft

NOVEMBER 10, 2021

At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store. Traditional data warehouse platform architecture. Data lake architecture example. Poor data quality, reliability, and integrity.

Architecture 52

Architecture Data Storage Machine Learning 52

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. process data in real time and run streaming analytics.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

Altexsoft

SEPTEMBER 23, 2021

The larger the company, the more data it has to generate actionable insights. Yet, more than often, businesses can’t make use of their most valuable asset — information. Because it is scattered across disparate systems, hardly available for analytical apps. A data warehouse (DW) is a unified storage for all corporate data.

Architecture 52

Architecture Data Storage IoT 52

CTOvision

JUNE 22, 2015

Commissioner Goodell has thrown significant support behind the activity, including several strategic investments around analytic capabilities to empower the fantasy sports enthusiast. The platform leverages the SAP HANA Cloud Platform, an in memory database and analytics engine, and SAP Lumira, a powerful cloud based data visualization suite.

Sport 116

Sport Comparison Internet Games 116

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 Azure Data Center 49

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?

Machine Learning 52

Machine Learning Artificial Inteligence Data Systems Review 52

Altexsoft

OCTOBER 2, 2020

Specialist responsible for the area: data architect, data engineer, ETL developer. Companies acquire data from multiple sources — manual entries, IoT devices, payment processors, CRMs, CMSs, eCommerce platforms, web and mobile analytics tools, social media. There are two main approaches to data integration.

Database Administration 64

Database Administration Strategy Data Technical Review 64

CIO

JANUARY 20, 2023

Topping the list of executive priorities for 2023—a year heralded by escalating economic woes and climate risks—is the need for data driven insights to propel efficiency, resiliency, and other key initiatives. Many companies have been experimenting with advanced analytics and artificial intelligence (AI) to fill this need.

Analytics 342

Analytics Artificial Inteligence Artificial Intelligence Hardware 342

Apiumhub

AUGUST 28, 2018

It is a cloud-based big data analytics platform, built to improve data-driven decision making. Cystellar’s platform provides predictive analytics to sectors such as insurtech, particularly helping insurers and their clients avoid damaging events. IOT projects that may change the world. ThreatInformer.

Insurance 95

Insurance Technical Review Artificial Inteligence Policies 95

Altexsoft

FEBRUARY 24, 2023

It also minimizes unplanned outages, which may disrupt businesses dependent on event streaming and real-time analytics. The shift to non-application jobs driven by the ability to support various types of workloads turns Kubernetes into a universal platform for almost everything and a de-facto operating system for cloud-native software.

Weak Development Team 83

Weak Development Team Load Balancer Technical Review Microservices 83

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. All in one, it significantly accelerates the processing of vast amounts of data.

Systems Review 85

Systems Review System Software Review Open Source 85

Altexsoft

OCTOBER 24, 2019

With a data warehouse, an enterprise is able to manage huge data sets, without administering multiple databases. 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. Subject-oriented data.

Architecture 50

Architecture Enterprise Data Technical Review 50

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. The term “ML” is No.

Conference 8

Conference Data Data Engineering Artificial Inteligence 8

Datavail

JANUARY 13, 2020

Amazon Redshift is among the best solutions to consider for cost-effectively creating a cloud-based data warehouse. Redshift is a fully-managed big data warehousing product from Amazon Web Services (AWS), built specifically to cost-effectively collect and store up to one petabyte of data in the cloud. Log Analytics.

Data 10

Data AWS Big Data Storage 10

Altexsoft

DECEMBER 9, 2020

In the era of global digital transformation , the role of data analysis in decision-making increases greatly. Still, today, according to Deloitte research, insight-driven companies are fewer than those not using an analytical approach to decision-making, even though the majority agrees on its importance. Stages of analytics maturity.

Analytics 102

Analytics Technical Review Technology Applications 102

Sunflower Lab

APRIL 2, 2024

Imagine a business world where your decisions are not just guided by past data, they are turbo-charged by insights that peer into the future, giving you a strategic advantage that feels almost unfair. That’s where predictive analytics with Power BI swoops in, taking center stage as a game-changer for CEO decision-making.

Analytics 40

Analytics Machine Learning Artificial Inteligence Analysis 40

Apiumhub

APRIL 8, 2021

Adrian specializes in mapping the Database Management System (DBMS), Big Data and NoSQL product landscapes and opportunities. Ronald van Loon has been recognized among the top 10 global influencers in Big Data, analytics, IoT, BI, and data science. Ronald van Loon. Kirk Borne. Marcus Borba.

Artificial Inteligence 109

Artificial Inteligence Technical Advisors Data Machine Learning 109

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.

Big Data 52

Big Data Analytics Data Analysis 52