Hu's Place - HitachiVantara

APRIL 11, 2019

According to the Harvard Business Review , " Cross-industry studies show that on average, less than half of an organization’s structured data is actively used in making decisions—and less than 1% of its unstructured data is analyzed or used at all. However, large data hubs over the last 25 years (e.g.,

Data Engineering 81

Data Engineering Machine Learning Artificial Inteligence Technical Review 81

Hu's Place - HitachiVantara

NOVEMBER 11, 2018

REAN Cloud is a global cloud systems integrator, managed services provider and solutions developer of cloud-native applications across big data, machine learning and emerging internet of things (IoT) spaces. This April, 47Lining, announced its Amazon Web Services (AWS) Industrial Time Series Data Connector Quick Start.

Cloud 78

Cloud Google Cloud Azure AWS 78

CTOvision

FEBRUARY 23, 2017

This is the place to dive deep into the latest on Big Data, Analytics, Artificial Intelligence, IoT, and the massive cybersecurity issues in all those topics. The data industry is growing fast, and Strata + Hadoop World has grown right along with it. Data scientists. Data engineers.

Big Data 61

Big Data Artificial Intelligence Artificial Inteligence Case Study 61

CTOvision

JUNE 15, 2015

They also launched a plan to train over a million data scientists and data engineers on Spark. ARMONK, NY - 15 Jun 2015: IBM (NYSE:IBM) today announced a major commitment to Apache®Spark™, potentially the most important new open source project in a decade that is being defined by data.

Open Source 117

Open Source Big Data Machine Learning Artificial Inteligence 117

Mobilunity

MAY 8, 2023

Key zones of an Enterprise Data Lake Architecture typically include ingestion zone, storage zone, processing zone, analytics zone, and governance zone. Ingestion zone is where data is collected from various sources and ingested into the data lake. Storage zone is where the raw data is stored in its original format.

Engineering 52

Engineering Data Storage AWS 52

Cloudera

JANUARY 19, 2018

There’s more data coming, and there are plenty of impossible things to work on. Machine Learning in the Age of Big Data. From its origins in the 1950’s to today, the age of big data. Sean ascertains that larger data sets and increased access to compute power is propelling the adoption of machine learning.

Artificial Inteligence 45

Artificial Inteligence Machine Learning Big Data IoT 45

Trigent

NOVEMBER 3, 2022

Logistics has been one of those industries where digitalization has been long overdue, although the linchpin holds several value chains together. Thankfully, it’s now a game for new technologies and leveraging structured and unstructured data like no other. Data analytics is not new to us anymore. Enhance transparency.

Analytics 52

Analytics Data IoT Trends 52

Altexsoft

MARCH 16, 2021

In this article, we will explain the concept and usage of Big Data in the healthcare industry and talk about its sources, applications, and implementation challenges. What is Big Data and its sources in healthcare? So, what is Big Data, and what actually makes it Big? But what happens next?

Big Data 116

Big Data Healthcare Applications Data 116

Cloudera

JANUARY 20, 2021

Digital transformation is a hot topic for all markets and industries as it’s delivering value with explosive growth rates. We have simplified this journey into five discrete steps with a common sixth step speaking to data security and governance. Data Collection Using Cloudera Data Platform.

Data 106

Data Artificial Inteligence Analytics Machine Learning 106

Apiumhub

JUNE 22, 2021

Data Innovation Summit topics. Data Innovation Summit: networking platform. The Data Innovation Summit is a great opportunity not only to learn but to meet your peers from other organisations, industries and sectors in the Nordic and beyond.

Innovation 84

Innovation Data Technical Review Artificial Inteligence 84

ParkMyCloud

DECEMBER 11, 2020

Coursera includes a number of free courses including topics in Machine Learning, Architecting, Data Engineering, Developing Applications, and the list goes on. . Their YouTube channel is a “gateway to high-quality videos, webinars, sample classes and lectures from industry practitioners and influencers.” Plural Sight.

Google Cloud 97

Google Cloud Training Resources Cloud 97

Hu's Place - HitachiVantara

JANUARY 3, 2019

” Deployments of large data hubs have only resulted in more data silos that are not easily understood, related, or shared. In order to utilize the wealth of data that they already have, companies will be looking for solutions that will give comprehensive access to data from many sources.

Trends 86

Trends Artificial Inteligence Data Center Machine Learning 86

Altexsoft

AUGUST 29, 2023

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

Architecture 52

Architecture Data Storage Machine Learning 52

Confluent

FEBRUARY 6, 2019

This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers. Impedance mismatch between data scientists, data engineers and production engineers. For now, we’ll focus on Kafka.

Machine Learning 106

Machine Learning Artificial Inteligence Scalability Data Engineering 106

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 can start investing in data infrastructure and analytical pipelines to automate data collection and analysis mechanisms. Customer data is heavily regulated.

Insurance 88

Insurance Machine Learning Artificial Inteligence Policies 88

Altexsoft

JULY 23, 2020

It facilitates collaboration between a data science team and IT professionals, and thus combines skills, techniques, and tools used in data engineering, machine learning, and DevOps — a predecessor of MLOps in the world of software development. MLOps lies at the confluence of ML, data engineering, and DevOps.

Artificial Inteligence 145

Artificial Inteligence Machine Learning DevOps Tools 145

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.

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

JUNE 25, 2019

If we look at the hierarchy of needs in data science implementations, we’ll see that the next step after gathering your data for analysis is data engineering. This discipline is not to be underestimated, as it enables effective data storing and reliable data flow while taking charge of the infrastructure.

Data Engineering 106

Data Engineering Engineering Data Artificial Inteligence 106

Cloudera

MAY 10, 2018

With advancements in exploratory data science, machine learning, predictive analytics, AI, and data engineering, the world is increasingly driven by data. This shift has created an unprecedented opportunity for disruption and problem-solving across industries. Business transformation. How to Enter.

Data 41

Data Machine Learning Artificial Inteligence Data Engineering 41

Coforge

AUGUST 31, 2020

With over 5 Trillion USD in gross insurance premiums, the global Insurance industry is on a digital journey to reshape the future of how it interacts with its customers to provide them with a differentiated experience. Grow — Navigating a Successful Path for Digitization.

Insurance 40

Insurance Technology Artificial Inteligence Policies 40

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

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. Source: slideshare.net/SparkSummit.

Analytics 20

Analytics Data IoT Analysis 20

Cloudera

FEBRUARY 19, 2018

With a modern, top-notch, in-memory columnar database it offers full coverage of all major industries and business processes, from data entry to finance, legal, compliance, production planning, and HR. It’s the de facto choice for all major corporations on the planet to manage their business data.

Data 46

Data Government Big Data Compliance 46

CIO

OCTOBER 18, 2023

German healthcare company Fresenius Medical Care, which specializes in providing kidney dialysis services, is using a combination of near real-time IoT data and clinical data to predict one of the most common complications of the procedure. CIO 100, Digital Transformation, Healthcare Industry, Predictive Analytics

Artificial Inteligence 334

Artificial Inteligence Analytics Artificial Intelligence Machine Learning 334

Existek

JANUARY 11, 2022

Cloud solutions have become unquestionably crucial for many industries and businesses. At some point, cloud computing has changed how to streamline business processes and deal with data in general. The tremendous popularity across all industries also explains the high cloud services distribution. Azure vs AWS: which is better?

Azure 52

Azure AWS Cloud How To 52

ParkMyCloud

JANUARY 17, 2020

The four different categories/levels of certifications include: Foundational: individuals should have at least six months of basic/foundational industry and AWS knowledge. AWS Certified Big Data – Speciality. For individuals who perform complex Big Data analyses and have at least two years of experience using AWS.

Google Cloud 9

Google Cloud Azure AWS Cloud 9

ParkMyCloud

MAY 29, 2019

There is exponential growth in the cloud computing industry, so it’s no surprise that the demand for cloud computing intellect and skills is also increasing, with no slowing down in the foreseeable future. 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

Apiumhub

APRIL 5, 2022

With over 1000 practical case studies presented on the past 6 editions and with new geo events in the MEA and the APAC region, the event is a worldwide movement, ushering the community of data, analytics and AI practitioners across functions, companies, industries, sectors, countries and regions to collaborate, benchmark, share and innovate.

Innovation 52

Innovation Data Artificial Inteligence Case Study 52

Altexsoft

FEBRUARY 8, 2021

Supply chain practitioners and CEOs surveyed by 6river share that the main challenges of the industry are: keeping up with the rapidly changing customer demand, dealing with delays and disruptions, inefficient planning, lack of automation, rising costs (of transportation, labor, etc.), Cost control. Shipment tracking and vehicle maintenance.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

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

Cloudera

MARCH 6, 2018

Indeed, industry analyst firm Enterprise Management Associates (EMA) found the number one barrier to cloud was increased complexity. Altus SDX enables companies to more easily build and deploy high-value applications for customer analytics, IoT, cyber-security, and more. Nimbly run many distinct applications against shared data.

Analytics 40

Analytics Cloud Big Data AWS 40

BPM

JANUARY 18, 2019

Regulated and unregulated industries should advance with caution. Without BIG CHANGES, many risk-averse organizations will slowly or rapidly disappear into self-imposed oblivion. Let's be honest - what we expect from the New Year predictions is this: "in year 20xx, the BPM industry will rocket right into the sky" :).

Artificial Inteligence 111

Artificial Inteligence Artificial Intelligence Machine Learning Weak Development Team 111

Altexsoft

OCTOBER 21, 2022

It offers high throughput, low latency, and scalability that meets the requirements of Big Data. The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. cloud data warehouses — for example, Snowflake , Google BigQuery, and Amazon Redshift.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

Altexsoft

OCTOBER 26, 2022

This can be anything from CRMs to AI-powered chatbots to IoT systems. The specific requirements for a CDO skillset vary depending on the industry in which they work. To make better digital transformation decisions, a CDO must know how modern technologies work, including such areas as machine learning, data engineering , and IoT.

CTO 52

CTO Organization Technical Review Culture 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. For this task, you need a dedicated specialist — a data engineer or ETL developer.

Machine Learning 52

Machine Learning Artificial Inteligence Data Systems Review 52

TIBCO - Connected Intelligence

AUGUST 10, 2020

Taking action to leverage your data is a multi-step journey, outlined below: First, you have to recognize that sticking to the status quo is not an option. Your data demands, like your data itself, are outpacing your data engineering methods and teams. Second, you have to decide what approach you want to take.

Virtualization 69

Virtualization Data How To Data Engineering 69