TechCrunch

SEPTEMBER 27, 2021

As more enterprises migrate to cloud-based architectures, they are also taking on more applications (because they can) and, as a result of that, more complex workloads and storage needs. Machine learning and other artificial intelligence applications add even more complexity.

Artificial Inteligence 246

Artificial Inteligence Applications Cloud Artificial Intelligence 246

CIO

JUNE 7, 2022

It comprises the processes, tools and techniques of data analysis and management, including the collection, organization, and storage of data. The chief aim of data analytics is to apply statistical analysis and technologies on data to find trends and solve problems. Data analytics methods and techniques.

Analytics 338

Analytics Data Analysis Business Analytics 338

Agile Engine

FEBRUARY 20, 2019

2018 was the second consecutive year when Gartner published an obituary of Big Data. No one, including Gartner, thinks Big Data is dead. Au contraire, Big Data has grown so ubiquitous it became “just data”, argue the authors of the obituaries. Trend 1: From Big Data to “Just Data”.

Big Data 71

Big Data Google Cloud Data Azure 71

Confluent

FEBRUARY 6, 2019

Building a scalable, reliable and performant machine learning (ML) infrastructure is not easy. It takes much more effort than just building an analytic model with Python and your favorite machine learning framework. Impedance mismatch between data scientists, data engineers and production engineers.

Machine Learning 106

Machine Learning Artificial Inteligence Scalability Data Engineering 106

d2iq

FEBRUARY 19, 2021

Except in many enterprises. Going from a prototype to production is perilous when it comes to machine learning: most initiatives fail , and for the few models that are ever deployed, it takes many months to do so. As little as 5% of the code of production machine learning systems is the model itself.

Artificial Inteligence 103

Artificial Inteligence Machine Learning Technical Review Software Review 103

CIO

FEBRUARY 14, 2023

To succeed with real-time AI, data ecosystems need to excel at handling fast-moving streams of events, operational data, and machine learning models to leverage insights and automate decision-making. It’s also used to deploy machine learning models, data streaming platforms, and databases.

Artificial Inteligence 290

Artificial Inteligence Strategy Data Machine Learning 290

Mobilunity

AUGUST 3, 2021

Big Data is a collection of data that is large in volume but still growing exponentially over time. It is so large in size and complexity that no traditional data management tools can store or manage it effectively. While Big Data has come far, its use is still growing and being explored.

Big Data 52

Big Data Data Engineering Engineering Data 52

CIO

MARCH 24, 2023

Whereas data governance is about the roles, responsibilities, and processes for ensuring accountability for and ownership of data assets, DAMA defines data management as “an overarching term that describes the processes used to plan, specify, enable, create, acquire, maintain, use, archive, retrieve, control, and purge data.”

Government 357

Government Data Technical Review Policies 357

KitelyTech

FEBRUARY 15, 2023

Here is a comprehensive overview of the three cloud platforms , highlighting their benefits and drawbacks, so you can decide which is best for your particular enterprise. Cloud computing is the process of storing and accessing data over the internet, rather than a computer’s hard drive. What Exactly is Cloud Computing?

Google Cloud 52

Google Cloud Azure AWS Cloud 52

CTOvision

JULY 9, 2014

The term “Big Data” has become synonymous with this evolution. But still, many of our customers continue to ask, “What is Big Data?”, “What are its use cases?”, What is Big Data? The data is too big, moves too fast, or does not fit the structures of your database architectures.

Big Data 114

Big Data Data CTO Fractional CTO 114

CIO

AUGUST 9, 2022

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines used by data scientists, data-centric applications, and other data consumers. Becoming a data engineer.

Data Engineering 328

Data Engineering Analytics Engineering Data 328

CIO

DECEMBER 4, 2023

Although less complex than the “4 Vs” of big data (velocity, veracity, volume, and variety), orienting to the variety and volume of a challenging puzzle is similar to what CIOs face with information management.

Artificial Inteligence 130

Artificial Inteligence Artificial Intelligence Sustainability Generative AI 130

Hu's Place - HitachiVantara

SEPTEMBER 4, 2018

Enterprise Storage Forum recently published their 2018 Storage Trends survey which made some interesting observations. The biggest challenges for IT and business leaders with operating their current storage infrastructure were aging equipment and lack of storage capacity. EB shipped in 1Q 2018. .”

Storage 53

Storage Performance IoT Machine Learning 53

Perficient

MARCH 19, 2024

If you have built or are building a Data Lake on the Google Cloud Platform (GCP) and BigQuery you already know that BigQuery is a fully managed enterprise data warehouse that helps you manage and analyze your data with built-in features like machine learning, geospatial analysis, and business intelligence.

Data 111

Data Google Cloud Analytics Serverless 111

AWS Machine Learning - AI

FEBRUARY 29, 2024

Knowledge Bases is completely serverless, so you don’t need to manage any infrastructure, and when using Knowledge Bases, you’re only charged for the models, vector databases and storage you use. RAG is a popular technique that combines the use of private data with large language models (LLMs).

Knowledge Base 110

Knowledge Base Artificial Inteligence Generative AI AWS 110

Infinidat

OCTOBER 4, 2023

The Cybersecurity and Infrastructure Security Agency (CISA) launched a new cybersecurity program to educate enterprises on how to stay cyber secure. Infinidat, as one of the Cybersecurity Awareness Month Champions , is dedicated to promoting a safer, more secure environment for our enterprise customers. The debate about it is over.

Storage 73

Storage Development Team Review Malware Systems Review 73

CIO

JUNE 7, 2023

This data in turn is used to train and serve machine learning models. These companies act on this data in the moment, serving millions of customers in real time. Let’s take a look at why Cassandra is the database of choice for organizations building enterprise-scale, real-time AI applications.

Organization 130

Organization Artificial Inteligence Open Source Architecture 130

AWS Machine Learning - AI

JANUARY 26, 2024

The goal of this post is to empower AI and machine learning (ML) engineers, data scientists, solutions architects, security teams, and other stakeholders to have a common mental model and framework to apply security best practices, allowing AI/ML teams to move fast without trading off security for speed.

Artificial Inteligence 120

Artificial Inteligence Generative AI Security Applications 120

Cloudera

FEBRUARY 7, 2019

A key pillar in the transformation journey is focused on robust data operations that can help ATB deliver timely, relevant and delightful service. The company sought a data management platform that would allow its enterprise to handle greater data variety, velocity and volume in a cost-effective manner.

Big Data 64

Big Data Analytics Google Cloud Cloud 64

CTOvision

FEBRUARY 20, 2015

Hortonworks'' Hadoop Data Platform (HDP) is now a supported feature on Google Cloud. This new feature will allow dynamic provisioning of HDP clusters on the Google Cloud Platform, providing scalability for enterprise-wide solutions employing HDP, as well as providing a means for rapidly setting up prototyping and development environments.

Google Cloud 108

Google Cloud Cloud Big Data Azure 108

Mobilunity

MAY 8, 2023

An Enterprise Data Lake is a large, centralized repository that stores structured and unstructured data at scale. It is designed to store vast amounts of data from a variety of sources. Moreover an Enterprise Data Lake makes it accessible to data scientists, analysts, and other users across the enterprise.

Engineering 52

Engineering Data Storage AWS 52

MagmaLabs

APRIL 25, 2023

Unlike an app, it loads rapidly, doesn’t eat into the storage space of devices, delivers a much better browsing experience, and users can access the app with just one click. The most recent top-funded AI businesses are all machine learning and chatbot companies, focusing on human interface with machines. billion U.S.

Trends 52

Trends eCommerce Artificial Inteligence Software 52

MagmaLabs

APRIL 25, 2023

Unlike an app, it loads rapidly, doesn’t eat into the storage space of devices, delivers a much better browsing experience, and users can access the app with just one click. The most recent top-funded AI businesses are all machine learning and chatbot companies, focusing on human interface with machines. billion U.S.

Trends 52

Trends eCommerce Artificial Inteligence Software 52

Altexsoft

FEBRUARY 11, 2023

The 11th annual survey of Chief Data Officers (CDOs) and Chief Data and Analytics Officers reveals 82 percent of organizations are planning to increase their investments in data modernization in 2023. What’s more, investing in data products, as well as in AI and machine learning was clearly indicated as a priority.

Data 87

Data Data Engineering Big Data Architecture 87

Apiumhub

MARCH 23, 2021

Data lakes really became the cornerstones of modern big data architecture. What is Data Lake? A data lake is a centralized repository that allows you to store all of your structured and unstructured data at any scale. It holds a large amount of raw data in its native form until businesses identify its use.

Architecture 52

Architecture Artificial Inteligence Data 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. Building an AI or machine learning model is not a one-time effort.

Trends 86

Trends Artificial Inteligence Data Center Machine Learning 86

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

Cloudera

JANUARY 26, 2022

According to 451 Research , 96% of enterprises are actively pursuing a hybrid IT strategy. Modern, real-time businesses require accelerated cycles of innovation that are expensive and difficult to maintain with legacy data platforms. The amount of data being collected grew, and the first data warehouses were developed.

Cloud 83

Cloud Data Architecture Virtualization 83

OTS Solutions

DECEMBER 22, 2023

Overview of Digital Transformation Digital transformation means the operational, cultural, and organizational changes within an organization’s ecosystem with the help of modern technologies such as cloud computing, the Internet of Things, artificial intelligence, machine learning, mobile apps, etc.

Artificial Inteligence 130

Artificial Inteligence Technical Review Artificial Intelligence Weak Development Team 130

Openxcell

DECEMBER 18, 2023

Benefits of using AI in app development Implementing Artificial Intelligence (AI) into applications delivers a host of benefits that enhance user experience and provide innovative solutions for enterprises. However, with AI tools, one can simply reduce the time to analyze this data by many fractions. How to develop an AI?

Artificial Inteligence 52

Artificial Inteligence Applications Development Artificial Intelligence 52

Hu's Place - HitachiVantara

APRIL 11, 2019

Few Data Management Frameworks are Business Focused Data management has been around since the beginning of IT, and a lot of technology has been focused on big data deployments, governance, best practices, tools, etc. However, large data hubs over the last 25 years (e.g., What has changed since then?

Data Engineering 81

Data Engineering Machine Learning Artificial Inteligence Technical Review 81

CTOvision

AUGUST 25, 2014

Leading organizations are changing the way they think about data with an enterprise data hub and driving everyday decisions and actions, from fraud prevention to insider threat analysis to exploratory analytics, with new information and new insights. Rethink Analytics. Register at: [link].

Analysis 98

Analysis Architecture Data Big Data 98

OTS Solutions

MAY 2, 2023

Cloud computing: Cloud computing has become a critical technology in Enterprise Digital Transformation. It enables businesses to store, access, and process data remotely via the Internet. Artificial intelligence and machine learning: Artificial and machine learning are critical technologies in digital transformation.

Artificial Inteligence 130

Artificial Inteligence Artificial Intelligence Machine Learning Blockchain 130

Kaseya

MAY 13, 2021

As the name suggests, a cloud service provider is essentially a third-party company that offers a cloud-based platform for application, infrastructure or storage services. In a public cloud, all of the hardware, software, networking and storage infrastructure is owned and managed by the cloud service provider. What Is a Public Cloud?

Google Cloud 122

Google Cloud Azure AWS Cloud 122

Cloudera

JANUARY 20, 2021

Reporting – delivering business enterprise insight (sales analysis and forecasting, market research, budgeting as examples). Predictive Analytics – predictive analytics based upon AI and machine learning (Fraud detection, predictive maintenance, demand based inventory optimization as examples).

Data 105

Data Artificial Inteligence Analytics Machine Learning 105

Cloudera

AUGUST 3, 2021

Advanced analytics and enterprise data are empowering several overarching initiatives in supply chain risk reduction – improved visibility and transparency into all aspects of the supply chain balanced with data governance and security. . Advanced analytics empower risk reduction . Improve Visibility within Supply Chains.

Analytics 108

Analytics Open Source Government Machine Learning 108

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. Customers demanded more from the start.

Data 90

Data Analytics Open Source Architecture 90