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

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 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

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 46

Artificial Inteligence Data Machine Learning Pharmaceuticals 46

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

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. Microsoft Azure.

Architecture 52

Architecture Cloud Storage Google Cloud 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

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. The result : optimized performance of emergency rooms.

Healthcare 72

Healthcare Analytics Examples Data 72

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

to see where freight is in real time and what the ETA is, share this information with customers, monitor and analyze fleet/carrier performance, and much more. Previously, control towers were seen as multi-faceted dashboards to monitor performance. The readings from IoT sensors and other connected devices (e.g.,

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

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

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

Altexsoft

FEBRUARY 22, 2022

Veteran truck drivers believe that “ If handled and driven correctly and the maintenance and inspections are performed religiously, you may never suffer a breakdown. ”. Data is gathered from connected sensors and analyzed so that predictions of possible failures can be generated.

Software Review 52

Software Review Technical Review Software Technology 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. High performance. How Apache Kafka streams relate to Franz Kafka’s books.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Open Source 93

Altexsoft

NOVEMBER 10, 2021

This enables different teams to use a single system to access all of the enterprise data for a range of projects, including data science, machine learning, and business intelligence. Let’s elaborate on this and figure out how a data lakehouse is different from its ancestors and name inspirers in more detail.

Architecture 52

Architecture Data Storage Machine Learning 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

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

CTOvision

JUNE 22, 2015

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. It contains data from every play that has ever happened in an NFL game and factors in statistical performance data along with details around player intangibles (injuries, rest, etc.)

Sport 116

Sport Comparison Internet Games 116

Altexsoft

FEBRUARY 24, 2023

Kubernetes load balancer to optimize performance and improve app stability The goal of load balancing is to evenly distribute incoming traffic across machines, enabling an app to remain stable and easily handle a large number of client requests. Tasks page is where you can learn how to perform basic operations with Kubernetes.

Weak Development Team 83

Weak Development Team Load Balancer Technical Review Microservices 83

Altexsoft

OCTOBER 2, 2020

Well-designed data management processes can yield big benefits for your business — such as follows. If properly organized, data management minimizes data movement, helps uncover performance breakdowns, and enables users to have all the necessary information a click away. 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. High performance. Additionally, it allows users to define their own data types.

Systems Review 85

Systems Review System Software Review Open Source 85

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. Cost Efficiency.

Data 10

Data AWS Big Data Storage 10

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 339

Analytics Artificial Inteligence Artificial Intelligence Hardware 339

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

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 109

Artificial Inteligence Technical Advisors Data Machine Learning 109

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.

Tools 16

Tools Data Technical Advisors Technical Review 16

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

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

Sunflower Lab

APRIL 2, 2024

For CEOs, predictive analytics is an essential tool because it enables them to know which clients are likely to buy certain products or services, how the market trends will play out in the future, and how the business is performing – information needed to make the right strategic decisions that will support growth and profitability.

Analytics 40

Analytics Machine Learning Artificial Inteligence Analysis 40

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

Altexsoft

MARCH 14, 2023

Data sources The first component of the MDS architecture is a place, or in most cases, places where your data originates from. Data may come from hundreds (or sometimes thousands) of different sources, including computers, smartphones, websites, social media networks, eCommerce platforms, and IoT devices.

Data 59

Data Technical Review Software Review Open Source 59