CIO

FEBRUARY 14, 2023

Organizations have balanced competing needs to make more efficient data-driven decisions and to build the technical infrastructure to support that goal. Achieving agility at scale with Kubernetes As organizations move into the real-time AI era, there is a critical need for agility at scale.

Artificial Inteligence 286

Artificial Inteligence Strategy Data Machine Learning 286

Kentik

NOVEMBER 21, 2016

And you’re up against an agile, innovative, and robust marketplace of players that are going for your network traffic jugular — and more. If DDoS has crossed the chasm with cloud-scale, innovative and agile approaches, why has DDoS protection lagged so far behind? But you can’t do that if you don’t have the data.

Big Data 40

Big Data Data B2C Storage 40

OTS Solutions

OCTOBER 10, 2023

also known as the Fourth Industrial Revolution, refers to the current trend of automation and data exchange in manufacturing technologies. It encompasses technologies such as the Internet of Things (IoT), artificial intelligence (AI), cloud computing , and big data analytics & insights to optimize the entire production process.

Artificial Inteligence 147

Artificial Inteligence Mobile Industry Cloud 147

Kaseya

NOVEMBER 9, 2023

With the cloud, users and organizations can access the same files and applications from almost any device since the computing and storage take place on servers in a data center instead of locally on the user device or in-house servers. The servers ensure an efficient allocation of computing resources to support diverse user needs.

Cloud 105

Cloud Disaster Recovery Artificial Inteligence Infrastructure 105

Cloudera

JUNE 13, 2023

In 2021, ANZ Bank unveiled its strategy to drive digital transformation, increase their speed to market and become more agile. To better handle future demands for advanced analytics, the project teams worked to reorganise the data using 70 servers for Data Discovery and 55 for Data Operations.

Analytics 76

Analytics Data Banking Big Data 76

TechCrunch

SEPTEMBER 28, 2022

The modern data stack consists of hundreds of tools for app development, data capture and integration, orchestration, analysis and storage. The two say that they saw an opportunity to create a platform that takes all the different big data workload granularities across an organization and presents them in a single pane of glass.

Data 204

Data Banking Machine Learning Artificial Inteligence 204

OTS Solutions

JUNE 2, 2023

has been transforming the manufacturing sector through the integration of advanced technologies such as artificial intelligence, the Internet of Things, and big data analytics. and Big Data Analytics in Predictive Maintenance Industry 4.0 is also enabling the use of big data in predictive maintenance.

Mobile 130

Mobile Artificial Inteligence Industry IoT 130

Infinidat

APRIL 26, 2022

By harnessing the unique operational awareness of InfiniVerse, IT teams have streamlined storage oversight and management to unprecedented levels of set-it-and-forget-it simplicity at their local site and across the globe. These insights simplify delivery of service levels and minimizes management of costs over the entire data lifecycle.

DevOps 98

DevOps Technology Storage SMB 98

OTS Solutions

DECEMBER 22, 2023

With the implementation of these technologies, you can achieve a more agile, customer-centric streamlined, and efficient business. Make better decisions: Companies can benefit from big data by putting analytics and data at the core of their digital transformation if the business does not.

Artificial Inteligence 130

Artificial Inteligence Technical Review Artificial Intelligence Weak Development Team 130

CIO

MARCH 24, 2023

A framework for managing data 10 master data management certifications that will pay off Big Data, Data and Information Security, Data Integration, Data Management, Data Mining, Data Science, IT Governance, IT Governance Frameworks, Master Data Management

Government 357

Government Data Technical Review Policies 357

TIBCO - Connected Intelligence

NOVEMBER 10, 2019

“The data universe is expanding. Launch yourself into a brave new data-driven world.” This year’s theme for Big Data LDN (London) challenges organizations to take a data-oriented approach to solve their biggest business challenges. Don’t miss the biggest data event of the year.

Big Data 20

Big Data Data Analytics Storage 20

Capgemini

MAY 20, 2020

Retailers have long been hampered by their data infrastructures, first by structural limitations inherent in data warehouses and then the expense and lack of agility of newer big-data systems. Companies need to find ways to get this cost down while improving the quality of data. .

Infrastructure 64

Infrastructure Data Retail Analytics 64

Xebia

JANUARY 19, 2023

The following quotes date back to those years: Data Engineers set up and operate the organization’s data infrastructure, preparing it for further analysis by data analysts and scientist. – AltexSoft All the data processing is done in Big Data frameworks like MapReduce, Spark and Flink.

Data Engineering 130

Data Engineering Engineering Data Technical Review 130

Capgemini

MAY 6, 2020

Many aspects of data management evolved in recent years, such as big data, data lakes, cloud-based storage and compute, self-service analytics, data streaming, AI/ML, etc. They brought in complexities to the data landscape but opened up opportunities for data democratization and self-service analytics.

Government 80

Government Data Retail Analytics 80

ProCal Tech

OCTOBER 2, 2022

Agility Planning a multi-cloud strategy is not an easy task. With the right expertise at hand, you will be able to achieve full speed and workflow between various cloud platforms, storage, and hypervisors. Many traditional companies are still struggling with legacy IT systems, existing buildings, and hardware providers.

Cloud 52

Cloud Disaster Recovery Storage Telecommunications 52

Altexsoft

JUNE 25, 2019

It’s necessary to figure out how to get sales data from its dedicated database talk with inventory records kept in a SQL server , for instance. This creates the necessity for integrating data in unified storage where data is collected, reformatted, and ready for use – data warehouse. Data warehouse storage.

Data Engineering 106

Data Engineering Engineering Data Artificial Inteligence 106

CTOvision

OCTOBER 27, 2014

The latest Palo Alto Networks VM-Series release provides organisations with the ability to realise the full agility and … Read more on Telecompaper (subscription). Big Data Product Watch 10/17/14: Big Three Make Big Moves. — dominated Big Data news this week, while the third, MapR Technologies Inc.,

Technical Review 103

Technical Review Technology Big Data Firewall 103

Cloudera

JANUARY 26, 2022

Network operating systems let computers communicate with each other; and data storage grew—a 5MB hard drive was considered limitless in 1983 (when compared to a magnetic drum with memory capacity of 10 kB from the 1960s). The amount of data being collected grew, and the first data warehouses were developed.

Cloud 82

Cloud Data Architecture Operating System 82

OverOps

APRIL 23, 2019

This exhilaration was primarily driven by the idea that the cloud could revamp businesses because of its innovation, cost savings and agility. Many organizations committed themselves to move complete data center applications onto the public cloud. Higher Level of Control Over Big Data Analytics.

Cloud 189

Cloud Data Center Architecture AWS 189

Trigent

FEBRUARY 15, 2023

Big Data / Fast Data – Do I need both? Big data is the vast amounts of structured and unstructured data generated from customer interactions, IoT devices, social media, and more. Big data insights are used to identify market trends, determine value propositions, and influence product design.

Data 52

Data Insurance Technical Review Big Data 52

Cloudera

SEPTEMBER 24, 2021

One of the most substantial big data workloads over the past fifteen years has been in the domain of telecom network analytics. The Dawn of Telco Big Data: 2007-2012. Suddenly, it was possible to build a data model of the network and create both a historical and predictive view of its behaviour. Learn more!

Analytics 90

Analytics Network Innovation IoT 90

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

Apiumhub

MARCH 23, 2021

The concept of Data lake architecture has recently become a hot topic. These days, businesses use data to define their internal business objectives and metrics. Data Lakes offer agile analytics to measure you are continually evolving business. Data lakes really became the cornerstones of modern big data architecture.

Architecture 52

Architecture Artificial Inteligence Data Machine Learning 52

CTOvision

FEBRUARY 4, 2015

If you are into technology and government and want to find ways to enhance your ability to serve big missions you need to be at this event, 25 Feb at the Hilton McLean Tysons Corner. Big data and its effect on the transformative power of data analytics are undeniable. Enabling Business Results with Big Data.

Fractional CTO 134

Fractional CTO Technical Review Big Data Analytics 134

Cloudera

SEPTEMBER 9, 2021

Cloudera Machine Learning or Cloudera Data Warehouse), to deliver fast data and analytics to downstream components. Infrastructure cost optimization by converting a fixed cost structure that previously consisted of infrastructure and cloud subscription costs per node into a variable cost model in the cloud based on actual consumption.

Storage 91

Storage Azure Technical Review Database Administration 91

Altexsoft

FEBRUARY 10, 2021

New approaches arise to speed up the transformation of raw data into useful insights. Similar to how DevOps once reshaped the software development landscape, another evolving methodology, DataOps, is currently changing Big Data analytics — and for the better. How DataOps relates to Agile, DevOps, and MLOps.

Analytics 75

Analytics DevOps Development Software Review 75

Datavail

FEBRUARY 11, 2020

Support for Big Data Operations. The sheer amount of data that companies collect and analyze is astronomical, so it’s important to have a database structure that works with you to derive value out of this information. Offers Columnar Storage for Faster Analytics Performance. Scaling Ad Hoc Data Requests.

Analytics 52

Analytics Database Administration Technical Review Storage 52

CTOvision

JANUARY 18, 2015

This popular gathering is designed to enable dialogue about business and technical strategies to leverage today’s big data platforms and applications to your advantage. Big data and its effect on the transformative power of data analytics are undeniable. Enabling Business Results with Big Data.

Fractional CTO 113

Fractional CTO Program Management Programming Big Data 113

The Crazy Programmer

SEPTEMBER 24, 2021

Handling this colossal data is tough; hence it requires NoSQL. These databases are more agile and provide scalable features; also, they are a better choice to handle the vast data of the customers and find crucial insights. It was mainly developed to solve scalability, and it is based on the Google Big Table.

Open Source 162

Open Source Scalability Firewall Linux 162

Apiumhub

MARCH 4, 2021

Data-as-a-service (DaaS) is a data management strategy and deployment model that focuses on the cloud to deliver a variety of data-related services such as storage, processing, and analytics. Since data service is the single update point, tracking changes to data is easier which can lead to data quality improvements.

Trends 72

Trends Data Analytics Business Intelligence 72

Datavail

JULY 7, 2022

Agility and scalability. Traditional on-premises analytics infrastructure is limited in terms of the agility and scalability that you can achieve. With finite hardware restrictions on computational power and storage, companies often struggle to adapt when facing unprecedented demand for analytics workloads. High data volumes.

Analytics 52

Analytics Artificial Inteligence Cloud Artificial Intelligence 52

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

Openxcell

JANUARY 6, 2023

Just a few of the existing cloud services include servers, storage, databases, networking, software, analytics, and business intelligence. Cloud storage functions by allowing users to access and download data on any selected device, such as a laptop, tablet, or smartphone, via an Internet service connection. Public cloud.

Architecture 52

Architecture Cloud Storage Google Cloud 52

O'Reilly Media - Data

SEPTEMBER 11, 2018

Containers want to be agile because that is the point of containers in the first place. First off, if your data is on a specialized storage appliance of some kind that lives in your data center, you have a boat anchor that is going to make it hard to move into the cloud. But there is a dark side here.

Big Data 150

Big Data Data Storage Software Review 150

iTexico

OCTOBER 27, 2020

This high value is based on analysis of where these specific technologies have the potential to increase revenue through better products and services, increase cost efficiency, speed, agility, and improve employee productivity. Your data and network infrastructure are among your most valuable assets in your company.

Technical Review 52

Technical Review Trends Enterprise Technology 52

Mobilunity

JANUARY 4, 2023

This is crucial because DevOps is now important for any organization that wants to be lean and agile in order to meet the needs of a market that is continually shifting. Infrastructure, including scalable storage, networking, server, mobile development, and cybersecurity solutions, is currently dominated by Amazon Web Services (AWS).

DevOps 52

DevOps How To Azure Weak Development Team 52

Trigent

MARCH 24, 2021

Integrating AI into IT operations or AIOps has empowered IT teams to perform complex tasks with ease and resolve agility issues in complex settings. Artificial intelligence, machine learning, big data have all been spoken about in great length and form the very backbone of Artificial Intelligence for IT operations or AIOps.

Artificial Inteligence 52

Artificial Inteligence Artificial Intelligence Machine Learning Infrastructure 52