AWS Machine Learning - AI

JANUARY 26, 2024

Many customers are looking for guidance on how to manage security, privacy, and compliance as they develop generative AI applications. In addition to awareness, your teams should take action to account for generative AI in governance, assurance, and compliance validation practices.

Artificial Inteligence 118

Artificial Inteligence Generative AI Security Applications 118

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

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 46

Artificial Inteligence Machine Learning Big Data IoT 46

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? Let’s see where it can come from.

Big Data 116

Big Data Healthcare Applications Data 116

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

Hu's Place - HitachiVantara

JANUARY 3, 2019

Public cloud, agile methodologies and devops, RESTful APIs, containers, analytics and machine learning are being adopted. ” Deployments of large data hubs have only resulted in more data silos that are not easily understood, related, or shared. Happy New Year and welcome to 2019, a year full of possibilities.

Trends 86

Trends Artificial Inteligence Data Center Machine Learning 86

Cloudera

AUGUST 31, 2021

Data warehousing is the backbone of every data driven organization , providing mission critical analytics. Today, modern data warehousing has evolved to meet the intensive demands of the newest analytics required for a business to be data driven. Migration of historical data from EDW Platform.

Data 85

Data Analytics Cloud Technical Review 85

Erik Bernhardsson

OCTOBER 27, 2015

I was featured in Peadar Coyle’s interview series interviewing various “data scientists” – which is kind of arguable since (a) all the other ppl in that series are much cooler than me (b) I’m not really a data scientist. What advice do you have to younger analytics professionals and in particular PhD students in the Sciences?

Data 100

Data Big Data Machine Learning Artificial Inteligence 100

Erik Bernhardsson

OCTOBER 27, 2015

I was featured in Peadar Coyle’s interview series interviewing various “data scientists” – which is kind of arguable since (a) all the other ppl in that series are much cooler than me (b) I’m not really a data scientist. What advice do you have to younger analytics professionals and in particular PhD students in the Sciences?

Data 100

Data Big Data Machine Learning Artificial Inteligence 100

Altexsoft

SEPTEMBER 9, 2022

In data science , metadata is one of the central aspects: It describes data (including unstructured data streams) fed into a big data analytical platform, capturing, for example, formats, file sizes, source of information, permission details, etc. Alation: support for self-service analytics and BI.

Tools 59

Tools Technical Review Software Review Systems Review 59

Capgemini

NOVEMBER 14, 2022

And they also need to trust that the data is current, relevant, and available. Moving a business forward requires fast access to good data for more applications. But that turns IT and analytics teams into the bottleneck. For self-service BI to succeed, however, the entire data value chain may need to be fixed.

Agile 52

Agile Technical Review Systems Review Artificial Intelligence 52

InfoWorld

FEBRUARY 9, 2024

Microsoft Fabric is an end-to-end, software-as-a-service (SaaS) platform for data analytics. It is built around a data lake called OneLake, and brings together new and existing components from Microsoft Power BI, Azure Synapse, and Azure Data Factory into a single integrated environment.

Big Data 80

Big Data Azure Google Cloud Data 80

Altexsoft

NOVEMBER 9, 2021

If you want to streamline your procurement and gain more visibility into this process, you have to get hold of available data, analyze it, and extract value to make informed decisions. What is procurement analytics and the opportunities it offers? Main components of procurement analytics. Procurement and its challenges.

Analytics 52

Analytics Software Review Systems Review Technical Review 52

Altexsoft

FEBRUARY 10, 2021

Similar to how DevOps once reshaped the software development landscape, another evolving methodology, DataOps, is currently changing Big Data analytics — and for the better. It covers the entire data analytics lifecycle, from data extraction to visualization and reporting, using Agile practices to speed up business results.

Analytics 75

Analytics DevOps Development Software Review 75

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. Governance. Cataloging.

Data 48

Data Government Big Data Compliance 48

Existek

JANUARY 11, 2022

The cloud computing market covers many areas like business processes, infrastructure, platform, security, management, analytics supported by cloud providers. Along with meeting customer needs for computing and storage, they continued extending services by presenting products dealing with analytics, Big Data, and IoT.

Azure 52

Azure AWS Cloud How To 52

Cloudera

MAY 10, 2018

Click to tweet : Nominations are now open for the sixth annual Cloudera Data Impact Awards! With advancements in exploratory data science, machine learning, predictive analytics, AI, and data engineering, the world is increasingly driven by data. Read how to get nominated. link] #DataImpactAwards.

Data 41

Data Machine Learning Artificial Inteligence Data Engineering 41

Altexsoft

JUNE 11, 2021

Process analytics takes place. Here, KPIs can be created and monitored to uncover potential improvement areas, data mining and/or ML algorithms can be used to detect hidden patterns and dependencies, or conformance checking techniques can be applied to compare the process to a certain ideal model. However, in reality, it took 52 days.

Applications 69

Applications Weak Development Team Systems Review Software Review 69

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

OCTOBER 29, 2020

But before you dive in, we recommend you reviewing our more beginner-friendly articles on data transformation: Complete Guide to Business Intelligence and Analytics: Strategy, Steps, Processes, and Tools. What is Data Engineering: Explaining the Data Pipeline, Data Warehouse, and Data Engineer Role.

Testing 63

Testing Tools Software Review Technical Review 63

CIO

AUGUST 18, 2022

Previously, Walgreens was attempting to perform that task with its data lake but faced two significant obstacles: cost and time. Those challenges are well-known to many organizations as they have sought to obtain analytical knowledge from their vast amounts of data. You can intuitively query the data from the data lake.

Data 350

Data Artificial Inteligence Technical Advisors Technical Review 350

Altexsoft

MARCH 18, 2021

It is the process of collecting raw data from disparate sources, transmitting it to a staging database for conversion, and loading prepared data into a unified destination system. These are data engineers who are responsible for implementing these processes. Data size and type. ELT comes to the rescue. What is ELT?

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

Cloudera

NOVEMBER 13, 2017

As the market moves toward cloud-based big data and analytics, three qualities emerge as vital for success. End-user focused tools accelerate daily tasks like job submission, performance tuning, and workload analytics. The net result is much improved productivity for data engineers, data scientists, and analysts.

Analytics 40

Analytics Cloud Big Data Machine Learning 40

Mobilunity

NOVEMBER 24, 2021

The demand for specialists who know how to process and structure data is growing exponentially. In most digital spheres, especially in fintech, where all business processes are tied to data processing, a good big data engineer is worth their weight in gold. Who Is an ETL Engineer?

Development 52

Development Storage Recruiting Architecture 52

Altexsoft

JANUARY 14, 2021

Non-volatile implies that once the data flies into a warehouse, it stays there and isn’t removed with new data enterings. As such, it is possible to retrieve old archived data if needed. Summarized touches upon the fact the data is used for data analytics. Data warehouse architecture.

Backup 115

Backup Azure Software Review Systems Review 115

Cloudera

FEBRUARY 11, 2019

The former sees growing investment in data analytics to become data-driven (45% of organizations expect to increase their spending in this area) while the latter is fueled by disruptive technology and the adoption of AI (41% of organizations name it as their game changer). Governing for compliance.

Government 59

Government Compliance Machine Learning Artificial Inteligence 59

Cloudera

AUGUST 24, 2020

Today we are continuing our discussion with Martin Mannion , EMEA Big Data Community lead at Deloitte and Paul Mackay, the EMEA Cloud Lead at Cloudera to look at why security and governance requirements must be tackled in the early stages of data-led use case development, thereby mitigating more work later on.

Cloud 80

Cloud Data Government Innovation 80

BPM

JANUARY 18, 2019

That augmentation must be in a form attractive to humans while enabling security, compliance, authenticity and auditability. 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. And herein lies the true challenge!'.

Artificial Inteligence 111

Artificial Inteligence Artificial Intelligence Machine Learning Weak Development Team 111

Altexsoft

NOVEMBER 5, 2021

So, we’ll only touch on its most vital aspects, instruments, and areas of interest — namely, data quality, patient identity, database administration, and compliance with privacy regulations. Cloud capabilities and HIPAA compliance out of the box. What is health information management: brief introduction the HIM landscape.

Technical Review 59

Technical Review Technology Software Review Healthcare 59

Altexsoft

NOVEMBER 10, 2021

A data lake is a repository to store huge amounts of raw data in its native formats ( structured, unstructured, and semi-structured ) and in open file formats such as Apache Parquet for further big data processing, analysis, and machine learning purposes. Key features of a data lakehouse. Lakehouse architecture.

Architecture 52

Architecture Data Storage Machine Learning 52

Cloudera

JUNE 4, 2018

Aspire , built by Search Technologies , part of Accenture is a search engine independent content processing framework for handling unstructured data. It provides a powerful solution for data preparation and publishing human-generated content to search engines and big data applications. compliance reporting.

Pharmaceuticals 47

Pharmaceuticals Data Big Data Systems Review 47

Datavail

MARCH 10, 2022

According to Gartner, only 20 percent of analytics insights will deliver business results through 2022. In other words, 80 percent of companies’ Big Data projects will fail and/or not deliver results. There are many reasons for this failure, but poor (or a complete lack of) data governance strategies is most often to blame.

Government 40

Government Strategy Weak Development Team Company 40

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

AUGUST 22, 2022

It is a general design approach that leverages data virtualization principles. Some of the tech companies pioneering the data fabric initiative are. Denodo, IBM with their IBM Cloud Pak for Data, Tibco Software, and. Consolidated data protection. In the data fabric vs data lake dilemma, everything is simple.

Architecture 52

Architecture Artificial Inteligence Technical Review Data 52

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

Altexsoft

MARCH 30, 2023

Along with thousands of other data-driven organizations from different industries, the above-mentioned leaders opted for Databrick to guide strategic business decisions. What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning.

Weak Development Team 64

Weak Development Team Machine Learning Artificial Inteligence Software Review 64

Altexsoft

MARCH 14, 2023

It must collect, analyze, and leverage large amounts of customer data from various sources, including booking history from a CRM system, search queries tracked with Google Analytics, and social media interactions. This means that companies don’t necessarily need a large data engineering team. Data democratization.

Data 59

Data Technical Review Software Review Artificial Inteligence 59