TIBCO - Connected Intelligence

APRIL 15, 2021

Data and analytics investments pay off. According to McKinsey, “High-performing organizations are three times more likely than others to say their data and analytics initiatives have contributed at least 20 percent to EBIT.” Twenty percent of earnings before interest and taxes from data and analytics alone!

Analytics 41

Analytics Development Team Review Technical Review Data 41

Hu's Place - HitachiVantara

APRIL 11, 2019

More than 70% of employees have access to data they should not, and 80% of analysts’ time is spent simply discovering and preparing data. Data breaches are common, rogue data sets propagate in silos, and companies’ data technology often isn’t up to the demands put on it."

Data Engineering 81

Data Engineering Machine Learning Artificial Inteligence Technical Review 81

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 20, 2021

Most of what is written though has to do with the enabling technology platforms (cloud or edge or point solutions like data warehouses) or use cases that are driving these benefits (predictive analytics applied to preventive maintenance, financial institution’s fraud detection, or predictive health monitoring as examples) not the underlying data.

Data 108

Data Artificial Inteligence Analytics Machine Learning 108

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.

Architecture 52

Architecture Data Storage Machine Learning 52

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

Capgemini

MAY 28, 2020

When the Capgemini Research Institute talked with manufacturers for the report Scaling AI in manufacturing operations: A practitioners’ perspective , the greatest amount of activity was in the maintenance (32%) and quality (26%) functions. The use of IoT sensors means manufacturers can access real-time data now.

Artificial Intelligence 52

Artificial Intelligence Artificial Inteligence Automotive Data Engineering 52

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

Cloudera

JANUARY 19, 2018

Sean ascertains that larger data sets and increased access to compute power is propelling the adoption of machine learning. General Data Protection Regulation (GDPR) and Data Science. Apache Kudu: Top Use Cases for Real-Time Analytics. Simplifying Big Data in the Cloud.

Artificial Inteligence 46

Artificial Inteligence Machine Learning Big Data IoT 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

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

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

AUGUST 25, 2020

That’s why a data specialist with big data skills is one of the most sought-after IT candidates. Data Engineering positions have grown by half and they typically require big data skills. Data engineering vs big data engineering. Big data processing. maintaining data pipeline.

Big Data 75

Big Data Data Engineering Engineering Data 75

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

Existek

JANUARY 11, 2022

The cloud computing market covers many areas like business processes, infrastructure, platform, security, management, analytics supported by cloud providers. Microsoft has reported a 51% growth in Azure public cloud revenue in the previous quarters. Data and analytics. Cloud migration and modernization.

Azure 52

Azure AWS Cloud How To 52

Coforge

AUGUST 31, 2020

Now, the power of data analytics along with smart automation can aid faster risk assessment and claim settlements. Augmented Customer Experience: According to Worldwide Insurance Survey by EFMA only 34% Gen Y customers reported a positive customer experience with their insurance provider.

Insurance 40

Insurance Technology Artificial Inteligence Policies 40

Cloudera

FEBRUARY 19, 2018

But when companies are looking towards new technologies such as data lakes, machine learning or predictive analytics, SAP alone is just not enough. To keep up with tech trends, businesses have to face the challenges of integrating SAP with non-SAP technologies and embark on a crusade against data silos.

Data 47

Data Government Big Data Compliance 47

DataRobot

APRIL 1, 2018

Paxata was a Silver Sponsor at the recent Gartner Data and Analytics Summit in Grapevine Texas. Although some product solutions disrupted the operational reporting market, they require users to know the questions they need to ask their data. 2) Line of business is taking a more active role in data projects.

Analytics 40

Analytics Artificial Inteligence Data Machine Learning 40

Altexsoft

MAY 14, 2021

And that’s the most important thing: Big Data analytics helps companies deal with business problems that couldn’t be solved with the help of traditional approaches and tools. 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

Altexsoft

MARCH 16, 2021

In general, a data infrastructure is a system of hardware and software tools used to collect, store, transfer, prepare, analyze, and visualize data. Check our article on data engineering to get a detailed understanding of the data pipeline and its components. Big data infrastructure in a nutshell.

Big Data 116

Big Data Healthcare Applications Data 116

Altexsoft

MARCH 31, 2020

It means you must collect transactional data and move it from the database that supports transactions to another system that can handle large volumes of data. Only after these actions can you analyze data with dedicated software (a so-called online analytical processing or OLAP system). But how do you move data?

Data 76

Data Storage Analytics Data Center 76

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. Work orders dashboard in Fleet Maintenance Pro.

Software Review 52

Software Review Technical Review Software Technology 52

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.

Tools 52

Tools Software Review Systems Review Testing 52

ParkMyCloud

MAY 29, 2019

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. IoT Engineer.

Trends 72

Trends Cloud IoT Artificial Inteligence 72

Altexsoft

JULY 19, 2022

She formulated the thesis in 2018 and published her first article “How to Move Beyond a Monolithic Data Lake to a Distributed Data Mesh” in 2019. So, to avoid any confusion, please be aware that data mesh is NOT. Some organizational approaches to analytics ownership are explained in our article about data science teams.

Architecture 52

Architecture Data Analytics Data Engineering 52

Confluent

JUNE 7, 2019

The Confluent Platform is an amazing toolbox, which every architect and data engineer should know of and utilize. Why does on-chain data matter? Any event, from IoT-supported delivery, trade, real estate transfer, to a bet in a prediction market is timestamped, censorship-resistant, and provable.

Blockchain 91

Blockchain Data Technical Review Software Review 91

Altexsoft

OCTOBER 26, 2022

Who reports to whom? With the initial introduction of the role, many companies had their CDOs report to CIOs (Chief Information Officers) and CTOs ( Chief Technology Officers ). These things can be measurable, so a CDO should calculate ROI and report the outcomes of the initiated digital projects. Attract talent.

CTO 52

CTO Organization Technical Review Culture 52

TIBCO - Connected Intelligence

DECEMBER 20, 2021

TIBCO Cloud Integration was identified as a “Leader” in four analyst reports, including the 2021 Gartner ® Magic Quadrant for EiPaaS , the Forrester Wave Enterprise iPaaS, Q4, 2021 , the 2021 Nucleus Research iPaaS Value Matrix , and the 2021 Aragon Research Globe Digital Business Business Platform Report.

Innovation 26

Innovation Analytics Virtualization Cloud 26

Altexsoft

OCTOBER 24, 2019

Enterprise data warehouse vs usual data warehouse: what’s the difference? Any data warehouse is a database which is always connected with raw-data sources via data integration tools on one end and analytical interfaces on the other. Reflects the source data. Subject-oriented data.

Architecture 50

Architecture Enterprise Data Technical Review 50

Altexsoft

SEPTEMBER 10, 2021

The pace of data being created is mind-blowing. For example, Amazon receives more than 66,000 orders per hour with each order containing valuable pieces of information for analytics. Yet, dealing with continuously growing volumes of data isn’t the only challenge businesses encounter on the way to better, faster decision-making.

Tools 52

Tools Data Software Review Technical Review 52

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. There are two main approaches to data integration.

Database Administration 64

Database Administration Strategy Data Technical Review 64

BPM

JANUARY 18, 2019

As we move into a world that is more and more dominated by technologies such as big data, IoT, and ML, more and more processes will be started by external events. Companies will start demanding that their investments in Predictive Analytics, Machine Learning and AI show a real ROI. Lloyd Dugan BPM.com [link].

Artificial Inteligence 111

Artificial Inteligence Artificial Intelligence Machine Learning Weak Development Team 111

Altexsoft

NOVEMBER 23, 2021

But this data is all over the place: It lives in the cloud, on social media platforms, in operational systems, and on websites, to name a few. Not to mention that additional sources are constantly being added through new initiatives like big data analytics , cloud-first, and legacy app modernization.

Virtualization 69

Virtualization Tools Data Architecture 69

Altexsoft

NOVEMBER 10, 2021

A data warehouse (DW) is a centralized repository for data accumulated from an array of corporate sources like CRMs, relational databases , flat files, etc. Typically used for data analysis and reporting, data warehouses rely on ETL mechanisms to extract , transform , and load data into a destination.

Architecture 52

Architecture Data Storage Machine Learning 52

Altexsoft

JUNE 7, 2021

The framework provides a way to divide a huge data collection into smaller chunks and shove them across interconnected computers or nodes that make up a Hadoop cluster. As a result, a Big Data analytics task is split up, with each machine performing its own little part in parallel. No real-time data processing.

Big Data 98

Big Data Tools Data Storage 98

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 Artificial Inteligence 8

Altexsoft

AUGUST 22, 2022

The landscape of enterprise data is fragmented. According to Flexera’s 2022 State of the Cloud Report , 89 percent of respondents have a multi-cloud strategy with 80 percent having a hybrid cloud approach in place. Organizations have data stored in public and private clouds, as well as in various on-premises data repositories.

Architecture 52

Architecture Artificial Inteligence Technical Review Data 52