Cloudera

MARCH 6, 2018

The real power in machine learning and analytics is when multiple analytics disciplines are able to work together in concert, sharing data in service of solving more complex and more valuable questions. Instead, they have separate data stores and inconsistent (if any) frameworks for data governance, management, and security.

Analytics 40

Analytics Cloud Big Data AWS 40

Cloudera

NOVEMBER 1, 2022

In the private sector, excluding highly regulated industries like financial services, the migration to the public cloud was the answer to most IT modernization woes, especially those around data, analytics, and storage. The post When Private Cloud is the Right Fit for Public Sector Missions appeared first on Cloudera Blog.

Cloud 87

Cloud Government Storage Analytics 87

Apiumhub

APRIL 8, 2021

We have created a list of people to help you eliminate unnecessary noise while staying connected to the Data Science community. The people listed promote learning and the sharing of knowledge by sharing their insights through LinkedIn, Twitter, blog posts, podcasts, books, workshops, etc. Ronald van Loon. Marcus Borba. Carla Gentry.

Artificial Inteligence 109

Artificial Inteligence Technical Advisors Data Machine Learning 109

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 107

Data Artificial Inteligence Analytics Machine Learning 107

Confluent

FEBRUARY 6, 2019

It takes much more effort than just building an analytic model with Python and your favorite machine learning framework. It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way. Impedance mismatch between data scientists, data engineers and production engineers.

Machine Learning 106

Machine Learning Artificial Inteligence Scalability Data Engineering 106

Datavail

JUNE 15, 2023

The Microsoft Fabric announcement at Microsoft Build 2023 has caused quite a stir in the data and analytics world. Microsoft Fabric is an all-in-one analytics solution that brings together seven Azure services on a shared SaaS foundation, in a unified experience combined with AI.

Azure 52

Azure Analytics Storage Generative AI 52

TIBCO - Connected Intelligence

OCTOBER 11, 2021

One example of an incredible solution fueled by TIBCO Partner-to-Partner is a new IoT solution developed by TIBCO, iSteer, and u-blox. With a broad portfolio of chips, modules, and secure data services and connectivity, u?blox Meet the Partners. The Solution in Action. Join TIBCO Partner-to-Partner.

IoT 49

IoT Wireless Healthcare Technical Review 49

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

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

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

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

Cloudera

OCTOBER 7, 2021

In this blog, I will demonstrate the value of Cloudera DataFlow (CDF) , the edge-to-cloud streaming data platform available on the Cloudera Data Platform (CDP) , as a Data integration and Democratization fabric. Data and Metadata: Data inputs and data outputs produced based on the application logic.

Architecture 124

Architecture Data Security Technical Review 124

ParkMyCloud

DECEMBER 11, 2020

With the combined knowledge from our previous blog posts on free training resources for AWS and Azure , you’ll be well on your way to expanding your cloud expertise and finding your own niche. Blogs & Forums. Blogs are a great way to keep your mind flowing with new insights, ideas, and the latest on all things cloud computing.

Google Cloud 97

Google Cloud Training Resources Cloud 97

Datavail

SEPTEMBER 8, 2022

According to an IDG survey , companies now use an average of more than 400 different data sources for their business intelligence and analytics processes. What’s more, 20 percent of these companies are using 1,000 or more sources, far too many to be properly managed by human data engineers. Conclusion.

Data 40

Data Nonprofit Quality Assurance Education 40

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. Definitely, the topic is way too extensive to be covered in a blog post, so we’re only going to make a succinct overview. What is Big Data and its sources in healthcare?

Big Data 116

Big Data Healthcare Applications Data 116

TIBCO - Connected Intelligence

DECEMBER 7, 2021

All of which poses a significant challenge for data architects to manage while still keeping organizations flexible and agile. As one of the fastest-growing trends in data and analytics, data fabrics have cemented themselves as a popular solution to today’s data challenges.

Architecture 49

Architecture Data Government Agile 49

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

Mobilunity

DECEMBER 28, 2022

Business intelligence involves using data analysis techniques to help businesses make better decisions about their operations and strategies. Statistical data analytics. IoT development. ML and AI freelance engineers are skilled in integrating ML with industrial IoT platforms featuring predictive capabilities.

Machine Learning 52

Machine Learning Artificial Inteligence Engineering How To 52

TIBCO - Connected Intelligence

MARCH 5, 2020

To help you answer these questions, in part one of this blog series I contrasted technology predictions (less than sure projections of the future) so prevalent at this time of year, versus sure technology bets (those things you can be 100% sure will happen). Data Is The Wisest Bet for 2020. And how do you raise your odds of success?

Technology 42

Technology Games Trends IoT 42

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. Learn more about the Data Impact Awards.

Data 41

Data Machine Learning Artificial Inteligence Data Engineering 41

Coforge

AUGUST 31, 2020

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Insurance 40

Insurance Technology Artificial Inteligence Policies 40

TIBCO - Connected Intelligence

DECEMBER 20, 2021

TIBCO DQ will become the new data quality product family, through an evolution of our current data quality offerings, significantly enhancing current capabilities available throughout the TIBCO data fabric with built-in AI and ML to automate quality, detection, monitoring, and anomaly resolution.

Innovation 26

Innovation Analytics Virtualization Cloud 26

Altexsoft

OCTOBER 21, 2022

The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. process data in real time and run streaming analytics. In other words, Kafka can serve as a messaging system, commit log, data integration tool, and stream processing platform. Kafka vs ETL.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

Kentik

DECEMBER 15, 2016

Needless to say, this call-out by analysts Nolan Greene and Rohit Mehra reflects well on what we’ve been doing to advance the state of the art in areas such as DDoS protection, infrastructure visibility, performance monitoring, and peering analytics. Why Kentik? That’s cloud-washing, a phenomenon that should be approached with wariness.

UI/UX 40

UI/UX Innovation Big Data Network 40

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]. 2019, oh my!

Artificial Inteligence 111

Artificial Inteligence Artificial Intelligence Machine Learning Weak Development Team 111

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 46

Data Government Big Data Compliance 46