CIO

FEBRUARY 13, 2023

This includes spending on strengthening cybersecurity (35%), improving customer service (32%) and improving data analytics for real-time business intelligence and customer insight (30%). On-prem infrastructure will grow cold — with the exception of storage, Nardecchia says.

Budget 363

Budget Artificial Inteligence Technical Review VR 363

Cloudera

DECEMBER 20, 2022

In this respect, several studies project that a proper use of advanced analytics implies savings of between 5% and 7.5%. The impact of the use of different analytical techniques in this field increases the profitability of these companies by 5% to 10%, at the same time increasing the brand value by increasing customer satisfaction.

Energy 81

Energy Analytics Data Machine Learning 81

The Crazy Programmer

NOVEMBER 6, 2021

IT or Information technology is the industry that has registered continuous growth. The Indian information Technology has attained about $194B in 2021 and has a 7% share in GDP growth. A cloud architect has a profound understanding of storage, servers, analytics, and many more. Big Data Engineer.

Artificial Inteligence 290

Artificial Inteligence Blockchain Artificial Intelligence Software Review 290

CIO

FEBRUARY 14, 2023

Streaming data technologies unlock the ability to capture insights and take instant action on data that’s flowing into your organization; they’re a building block for developing applications that can respond in real-time to user actions, security threats, or other events. report they have established a data culture 26.5%

Artificial Inteligence 289

Artificial Inteligence Strategy Data Machine Learning 289

Altexsoft

FEBRUARY 11, 2023

Data is now one of the most valuable assets for any kind of business. 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. Feel free to enjoy it. Feel free to enjoy it.

Data 87

Data Data Engineering Big Data Architecture 87

Cloudera

JULY 24, 2023

In their effort to reduce their technology spend, some organizations that leverage open source projects for advanced analytics often consider either building and maintaining their own runtime with the required data processing engines or retaining older, now obsolete, versions of legacy Cloudera runtimes (CDH or HDP).

Open Source 66

Open Source Analytics Software Review Metrics 66

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

Cloudera

NOVEMBER 1, 2022

A quick trip in the congressional time machine to revisit 2017’s Modernizing Government Technology Act surfaces some of the most salient points regarding agencies’ challenges: The federal government spends nearly 75% of its annual information technology funding on operating and maintaining existing legacy information technology systems.

Cloud 89

Cloud Government Storage Analytics 89

Kentik

APRIL 12, 2023

Data scientists play a critical role in the DataOps ecosystem, leveraging advanced analytics and machine learning techniques to gain insights from large and complex data sets. DataOps strategies require a robust data infrastructure, including data warehouses, data lakes, caches, and other data storage and processing systems.

Network 52

Network Data Engineering Machine Learning Artificial Inteligence 52

InnovationM

MAY 14, 2023

In this article, I will share practical insights and technologies utilized in building and harnessing the potential of data lakes. Demystifying Data Lakes Data lakes serve as flexible storage repositories, enabling organizations to store raw and diverse data types, breaking away from the constraints of traditional data warehouses.

Data 52

Data Storage Construction Business Intelligence 52

Dzone - DevOps

FEBRUARY 16, 2023

However, in today's era, what's more, important than the data itself is the ability to locate your wanted information among all the overflowing data quickly. So in this article, I will talk about how I improved overall data processing efficiency by optimizing the choice and usage of data warehouses.

Data 87

Data ChatGPT Storage Architecture 87

Hu's Place - HitachiVantara

MAY 24, 2019

The latest International Data Corporation ( IDC ) Worldwide Quarterly Enterprise Storage Systems Tracker , was published on March 4, 2019. It showed vendor revenue in the worldwide enterprise storage systems market is still increasing: 7.4% enterprise storage market in 4Q 2018. year over year to $14.5 This takes DataOps.

Marketing 75

Marketing Storage Systems Review Enterprise 75

Cloudera

NOVEMBER 16, 2022

A common theme that was highlighted continuously was using “storytelling” to relay the value that data and analytics teams bring to the business. This leads to a further challenge of the chief data and analytics officer’s role: Is the mission to play offense — drive revenue? Are you playing offense or defense?

Data 81

Data Insurance Metrics eBook 81

Apps Associates

JULY 28, 2022

Efficiently load and transform data at scale into Data Lakes for data science and analytics. Load the data into object storage and create high-quality models more quickly using OCI data science. Use Case 2: Data integration for data marts and data warehousing. Oracle Managed.

Infrastructure 52

Infrastructure Cloud Data Linux 52

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. Copyright © 2021 Accenture. All rights reserved.

Data 82

Data Analytics Cloud Technical Review 82

Confluent

FEBRUARY 6, 2019

It takes much more effort than just building an analytic model with Python and your favorite machine learning framework. This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers.

Machine Learning 106

Machine Learning Artificial Inteligence Scalability Data Engineering 106

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 means having information about their origin, journey, ownership, certifications, etc.,

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

Altexsoft

SEPTEMBER 9, 2022

Each card contained important information about one book that helped identify and locate it: name, author, date of creation or publication, subject coverage, and the library number. Or think of the nutritional information on the food packaging – it also lists the predetermined characteristics of the product inside. What is metadata?

Tools 59

Tools Technical Review Software Review Systems Review 59

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 110

Data Artificial Inteligence Analytics Machine Learning 110

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

Altexsoft

AUGUST 19, 2022

In our blog, we’ve been talking a lot about the importance of business intelligence (BI), data analytics, and data-driven culture for any company. Multiple studies continuously demonstrate the superiority of analytics-based organizations (e.g., You get 10GB of cloud storage and can upload 1GB of data at a time.

Weak Development Team 52

Weak Development Team Data Azure Analytics 52

Altexsoft

JANUARY 22, 2020

As a result, it became possible to provide real-time analytics by processing streamed data. Please note: this topic requires some general understanding of analytics and data engineering, so we suggest you read the following articles if you’re new to the topic: Data engineering overview.

Analytics 20

Analytics Data IoT Analysis 20

Cloudera

JANUARY 6, 2021

Python is used extensively among Data Engineers and Data Scientists to solve all sorts of problems from ETL/ELT pipelines to building machine learning models. Apache HBase is an effective data storage system for many workflows but accessing this data specifically through Python can be a struggle.

Machine Learning 133

Machine Learning Artificial Inteligence Data Applications 133

Kentik

JULY 18, 2016

But the value of that knowledge often remains buried because even experienced organizations have traditionally lacked the timely, comprehensive information required to yield actionable insights. Until now the tools available to generate and access such information have been limited at best. Ready to learn more about Kentik Detect?

Big Data 40

Big Data Network Analytics Data 40

Existek

JANUARY 11, 2022

The cloud computing market covers many areas like business processes, infrastructure, platform, security, management, analytics supported by cloud providers. In 2010, they launched Windows Azure, the PaaS, positioning it as an alternative to Google App Engine and Amazon EC2. Data and analytics. Internet of Things.

Azure 52

Azure AWS Cloud How To 52

RapidValue

JULY 21, 2019

In a world, which demands consumable data immediately but plagued by constant change and data drift, the traditional approach of designing, deploying and operating data pipelines as siloed activities is expensive and risky. There is a mass data movement to the cloud, taking big steps to consolidate analytics-ready data.

Business Transformation 65

Business Transformation Enterprise DevOps Analytics 65

Altexsoft

JUNE 14, 2021

Lemonade is a US insurance company that uses Maya – an AI-powered bot, to collect and analyze customer data. Maya acts as a virtual assistant that gets information, provides quotes, and handles payments. The groups are created using algorithms that collect extensive customer data, such as health conditions.

Insurance 88

Insurance Machine Learning Artificial Inteligence Policies 88

TIBCO - Connected Intelligence

APRIL 22, 2021

Does that figure seem excessive, especially when more copies mean more storage, which requires servers that consume yet more power? Granted, you need backups, but even if you back up all your new data twice, you still consume 50% more energy to store all the other extra copies. Some analytic tools query data efficiently.

Sustainability 46

Sustainability Virtualization Data Energy 46

TIBCO - Connected Intelligence

DECEMBER 11, 2020

We are a Nordic IT service company enabling our client’s data-driven business transformation. With our deep expertise across hybrid platforms, information management and applications, we bring together relevant data for more intelligent operations that drive long-term business value. It seems data is a key enabler.

Business Transformation 52

Business Transformation Data Analytics Hotels 52

KitelyTech

FEBRUARY 3, 2021

Today, big data is used extensively by companies all over the world for solving complicated problems regarding business development and marketing. Big data also helps to understand customer behavior by collecting information about users and their behaviors, which is important for online business development. Database Management.

Big Data 52

Big Data Data Development Business Intelligence 52

Altexsoft

APRIL 22, 2020

quintillion bytes of data generated daily, data scientists get busier than ever. The more information we have, the more we can do with it. And data science provides us with methods to make use of this data. We’ll also describe how data engineer’s are different from other related roles.

Data Engineering 69

Data Engineering Engineering Artificial Inteligence Data 69

AWS Machine Learning - AI

JANUARY 26, 2024

Being aware of risks fosters transparency and trust in generative AI applications, encourages increased observability, helps to meet compliance requirements, and facilitates informed decision-making by leaders.

Artificial Inteligence 115

Artificial Inteligence Generative AI Security Applications 115

Hu's Place - HitachiVantara

SEPTEMBER 26, 2018

I could see a similar transition in our industry where cloud was a threat to the IT vendors, but today the revenues are increasing for IT vendors due to software and services which makes it easier for their customers to develop applications and generate information. With greater access to data comes greater responsibility.

Software Review 60

Software Review Systems Review Technical Review Big Data 60

Altexsoft

AUGUST 25, 2020

What to consider big data and what is not so big data? Big data is still data, of course. But it requires a different engineering approach and not just because of its amount. Big data is tons of mixed, unstructured information that keeps piling up at high speed. Big data processing.

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

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. DataOps is a relatively new methodology that knits together data engineering, data analytics, and DevOps to deliver high-quality data products as fast as possible.

Analytics 75

Analytics DevOps Development Software Review 75

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. Summing up all of the above, source-to-pay processes suffer the most from information inaccuracies, lack of general picture, and inefficient planning.

Analytics 52

Analytics Software Review Systems Review Technical Review 52