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

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. Who needs a data lake?

Architecture 52

Architecture Data Storage Machine Learning 52

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

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 Blockchain Big Data Innovation 32

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

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

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. You’ll need a data engineering team for that. How data engineers and data platforms work. Customers are grouped according to their risk behaviors.

Insurance 88

Insurance Machine Learning Artificial Inteligence Policies 88

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. How an IoT system works.

IoT 141

IoT Azure AWS Transportation 141

Cloudera

SEPTEMBER 12, 2018

AbbVie, one of the world’s largest global research and development pharmaceutical companies, established a big data platform to provide end-to-end operations visibility, agility, and responsiveness. The lab uses Cloudera running on Cazena’s Fully-Managed Big Data as a Service on Amazon Web Services (AWS). Special Impact.

Artificial Inteligence 45

Artificial Inteligence Data Machine Learning Pharmaceuticals 45

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

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

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

AUGUST 31, 2020

The data is already being stored digitally: more than 95 percent of health facilities report implementing Electronic Health Records (EHR) systems. Large part of data comes from widely adopted IoT devices used in 60 percent of hospitals in the US today. Data analytics can also operate different sources.

Healthcare 72

Healthcare Analytics Examples Data 72

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

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

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

ParkMyCloud

MAY 29, 2019

Business Intelligence Analyst. BI Analyst can also be described as BI Developers, BI Managers, and Big Data Engineer or Data Scientist. IoT Engineer. The main responsibility of IoT engineers is to help businesses keep up with IoT technology trends. The Future of Cloud Computing Jobs.

Trends 72

Trends Cloud IoT Artificial Inteligence 72

Altexsoft

DECEMBER 23, 2022

One of the main reasons behind this is the need to timely process huge volumes of data in any format. As said, ETL and ELT are two approaches to moving and manipulating data from various sources for business intelligence. In ETL, all the transformations are done before the data is loaded into a destination system.

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. HealthTap APIs: mix of real-time chats, Big Data analytics, and prepared answers from doctors.

Tools 69

Tools Healthcare Insurance Video 69

CTOvision

AUGUST 17, 2017

IT teams are a core component of most modern businesses. Computers and the Internet are simply too important for any business to neglect them without running into serious problems. Unfortunately, building an effective IT team is often easier said than done.

Performance 61

Performance Internet Big Data IoT 61

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. Cloudera , focusing on Big Data analytics. Red Hat , acquired by IBM.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

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

CTOvision

JUNE 22, 2015

Rather than bolting on third party analysis tools to interact with data in the database, HANA provides a unified architecture including: libraries for predictive analytics, text processing, spatial analysis, and business intelligence, all operating against the data resident in memory within the HANA platform.

Sport 116

Sport Comparison Internet Games 116

Altexsoft

SEPTEMBER 23, 2021

The main purpose of a DW is to enable analytics: It is designed to source raw historical data, apply transformations, and store it in a structured format. This type of storage is a standard part of any business intelligence (BI) system, an analytical interface where users can query data to make business decisions.

Architecture 52

Architecture Data Storage IoT 52

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

Altexsoft

FEBRUARY 24, 2023

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. Framework Programming The Good and the Bad of Node.js Framework Programming The Good and the Bad of Node.js

Weak Development Team 83

Weak Development Team Load Balancer Technical Review Microservices 83

Altexsoft

OCTOBER 2, 2020

Data integration and interoperability: consolidating data into a single view. Specialist responsible for the area: data architect, data engineer, ETL developer. Scattered across different storages in various formats, data values don’t talk to each other. Snowflake data management processes.

Database Administration 64

Database Administration Strategy Data Technical Review 64

Apiumhub

AUGUST 28, 2018

It is a cloud-based big data analytics platform, built to improve data-driven decision making. CaseGlide is the leading case management system for insurance companies and their attorneys to streamline collaboration, automate routine processes, and create transformative business intelligence. The era of unicorns.

Insurance 96

Insurance Technical Review Artificial Inteligence Policies 96

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.

Data 10

Data AWS Big Data Storage 10

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. Stream” itself was No.

Conference 8

Conference Data Data Engineering Artificial Inteligence 8

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. It becomes even more important for enterprises operating big data applications.

Systems Review 85

Systems Review System Software Review Open Source 85

CIO

JANUARY 20, 2023

And modern object storage solutions, offer performance, scalability, resilience, and compatibility on a globally distributed architecture to support enterprise workloads such as cloud-native, archive, IoT, AI, and big data analytics. An organization’s data, applications and critical systems must be protected.

Analytics 336

Analytics Artificial Inteligence Artificial Intelligence Hardware 336

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. Cindi Howson.

Artificial Inteligence 110

Artificial Inteligence Technical Advisors Data Machine Learning 110

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.

Architecture 50

Architecture Enterprise Data Technical Review 50

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