Cookie Settings

By clicking "Agree," you consent to the storage of cookies on your device to enhance site navigation, analyze site usage, and support our marketing efforts. For more information, please refer to our Privacy Policy.

Reject
Agree
Glossary
Data Infrastructure

Google Cloud Platform (GCP)

GCP is a suite from Google, with services for computing, data processing, data analysis, machine learning, and artificial intelligence.

Meaning in detailContact us now

It provides a wide range of services for computing, data processing, data analysis, machine learning, and artificial intelligence. GCP is built on the same infrastructure that Google uses for its own end-user products, such as Google Search, Gmail, and YouTube.

Benefits of using GCP

  • Scalability: GCP services can be easily scaled to meet an organization's changing needs.
  • Reliability: GCP offers high reliability and availability.
  • Power: GCP services are high-performance and can handle even the most demanding workloads.
  • Innovation: Google is constantly investing in developing new GCP services and features.
  • Safety: GCP provides comprehensive security features to protect data and applications.
  • Costs: GCP offers a flexible pricing model that allows businesses to pay only for the services they use.

Key Google Cloud Platform services

  • Compute engine: Provides virtual machines (VMs) and containers to run applications in the cloud.
  • Google Kubernetes Engine (GKE): Provides a managed Kubernetes platform for running containerized applications
  • Cloud storage: Offers scalable object storage for storing data in the cloud.
  • BigQuery: Offers a data warehouse service for analyzing big data.
  • Cloud Spanner: Provides a globally distributed database for developing scalable, highly available applications.
  • Cloud AI platform: Offers a range of machine learning and artificial intelligence services.
  • Looker: Analyze regulated data, deliver business insights, and develop AI-powered applications

GCP and The Data Institute

The Data Institute can use GCP to achieve its data analysis- and to operate data science applications. GCP provides a variety of services that help Data scientists and analysts are useful, such as BigQuery, Cloud Spanner, and Cloud AI Platform. We are happy to support you with Data architecture, Data Organization or Machine learning services.

Further links:

Note: Our team benefited from the support of AI technologies while creating and maintaining this glossary.

Abstrakte Form eines Pfades

Contact now
Abstrakte Form eines Pfades

Do you have questions around
Google Cloud Platform (GCP)
?

Let´s TalkContactFollow us on LinkedIn

Passende Case Studies

Zu diesem Thema gibt es passende Case Studies

Alle Case Studies entdecken
Babymarkt is data-driven
eCommerce
5
Minuten Lesedauer

From data audit to individual architecture sketch

eCommerce thrives on data — babymarkt wanted to make even better use of it.
Couple reading a newspaper
Medien
5
Minuten Lesedauer

MediaPrint reinvents itself in terms of data technology

The publisher wanted a clear structure and the development of a data culture.
A modern data stack for in-depth customer analysis
eCommerce
4
Minuten Lesedauer

A modern data stack for in-depth customer analysis

Modern Data Stack is used for data integration to analyze customer behavior and product data
Development of recommendations for action through PoC implementation
Logistik
5
Minuten Lesedauer

PoC provides the basis for recommendations for action

The PoC forms the basis for further decisions to introduce a modern data platform.

Which services fit to
Google Cloud Platform (GCP)
?

<svg width=" 100%" height=" 100%" viewBox="0 0 62 62" fill="none" xmlns="http://www.w3.org/2000/svg"> <g clip-path="url(#clip0_5879_3245)"> <path d="M54.25 3.875H31C29.9726 3.87603 28.9876 4.28461 28.2611 5.01109C27.5346 5.73758 27.126 6.7226 27.125 7.75V27.125H7.75C6.7226 27.126 5.73758 27.5346 5.01109 28.2611C4.28461 28.9876 3.87603 29.9726 3.875 31V58.125H58.125V7.75C58.124 6.7226 57.7154 5.73758 56.9889 5.01109C56.2624 4.28461 55.2774 3.87603 54.25 3.875ZM17.4375 54.25V40.6875H25.1875V54.25H17.4375ZM54.25 54.25H29.0625V38.75C29.0625 38.2361 28.8584 37.7433 28.495 37.38C28.1317 37.0166 27.6389 36.8125 27.125 36.8125H15.5C14.9861 36.8125 14.4933 37.0166 14.13 37.38C13.7666 37.7433 13.5625 38.2361 13.5625 38.75V54.25H7.75V31H31V7.75H54.25V54.25Z" fill="currentColor"/> <path d="M34.875 15.5H38.75V19.375H34.875V15.5ZM46.5 15.5H50.375V19.375H46.5V15.5ZM34.875 27.125H38.75V31H34.875V27.125ZM46.5 27.125H50.375V31H46.5V27.125ZM34.875 38.75H38.75V42.625H34.875V38.75ZM46.5 38.75H50.375V42.625H46.5V38.75Z" fill="currentColor"/> </g> <defs> <clipPath id="clip0_5879_3245"> <rect width="62" height="62" fill="currentColor"/> </clipPath> </defs> </svg>

Data Architecture

The right tools in the right place. Update the existing infrastructure or renew most of it.

<svg width=" 100%" height=" 100%" viewBox="0 0 62 62" fill="none" xmlns="http://www.w3.org/2000/svg"> <g clip-path="url(#clip0_5879_2705)"> <path d="M7.75 50.375H15.5V58.125H7.75V50.375ZM27.125 50.375H34.875V58.125H27.125V50.375ZM46.5 50.375H54.25V58.125H46.5V50.375ZM48.4375 31H32.9375V27.125H29.0625V31H13.5625C12.5351 31.001 11.5501 31.4096 10.8236 32.1361C10.0971 32.8626 9.68853 33.8476 9.6875 34.875V46.5H13.5625V34.875H29.0625V46.5H32.9375V34.875H48.4375V46.5H52.3125V34.875C52.3115 33.8476 51.9029 32.8626 51.1764 32.1361C50.4499 31.4096 49.4649 31.001 48.4375 31ZM17.4375 3.875V23.25H44.5625V3.875H17.4375ZM21.3125 7.75H25.1875V19.375H21.3125V7.75ZM40.6875 19.375H29.0625V7.75H40.6875V19.375Z" fill="currentColor"/> </g> <defs> <clipPath id="clip0_5879_2705"> <rect width="62" height="62" fill="currentColor"/> </clipPath> </defs> </svg>

Data Organization

So that the handling and responsibility of data is structured and everyone knows its responsibilities.

<svg width=" 100%" height=" 100%" viewBox="0 0 62 62" fill="none" xmlns="http://www.w3.org/2000/svg"> <g clip-path="url(#clip0_5994_7571)"> <path d="M52.3125 46.5C51.4494 46.5039 50.5984 46.7026 49.8228 47.0813L41.4916 38.75H34.875V42.625H39.8854L47.0832 49.8228C46.7043 50.5984 46.505 51.4494 46.5 52.3125C46.5 53.4621 46.8409 54.5859 47.4796 55.5418C48.1183 56.4976 49.0261 57.2426 50.0882 57.6826C51.1502 58.1225 52.3189 58.2376 53.4465 58.0133C54.574 57.789 55.6097 57.2355 56.4226 56.4226C57.2355 55.6097 57.789 54.574 58.0133 53.4465C58.2376 52.319 58.1225 51.1503 57.6825 50.0882C57.2426 49.0261 56.4976 48.1183 55.5417 47.4796C54.5859 46.8409 53.4621 46.5 52.3125 46.5ZM52.3125 54.25C51.9293 54.25 51.5547 54.1364 51.2361 53.9235C50.9175 53.7106 50.6691 53.408 50.5225 53.054C50.3758 52.6999 50.3375 52.3104 50.4122 51.9345C50.487 51.5587 50.6715 51.2135 50.9425 50.9425C51.2134 50.6715 51.5587 50.487 51.9345 50.4122C52.3103 50.3375 52.6999 50.3758 53.0539 50.5225C53.408 50.6691 53.7106 50.9175 53.9235 51.2361C54.1364 51.5547 54.25 51.9293 54.25 52.3125C54.25 52.8264 54.0459 53.3192 53.6825 53.6825C53.3192 54.0459 52.8264 54.25 52.3125 54.25ZM52.3125 25.1875C51.1143 25.1911 49.9465 25.5655 48.9696 26.2593C47.9927 26.9531 47.2546 27.9323 46.8565 29.0625H34.875V32.9375H46.8565C47.2134 33.9395 47.8389 34.8242 48.6646 35.4948C49.4903 36.1653 50.4845 36.5961 51.5384 36.7399C52.5923 36.8837 53.6655 36.735 54.6407 36.3101C55.6158 35.8852 56.4554 35.2005 57.0678 34.3307C57.6801 33.4609 58.0416 32.4396 58.1127 31.3783C58.1838 30.317 57.9618 29.2565 57.471 28.3128C56.9802 27.3691 56.2395 26.5785 55.3297 26.0273C54.42 25.4761 53.3762 25.1856 52.3125 25.1875ZM52.3125 32.9375C51.9293 32.9375 51.5547 32.8239 51.2361 32.611C50.9175 32.3981 50.6691 32.0955 50.5225 31.7415C50.3758 31.3874 50.3375 30.9979 50.4122 30.622C50.487 30.2462 50.6715 29.9009 50.9425 29.63C51.2134 29.359 51.5587 29.1745 51.9345 29.0997C52.3103 29.025 52.6999 29.0633 53.0539 29.21C53.408 29.3566 53.7106 29.605 53.9235 29.9236C54.1364 30.2422 54.25 30.6168 54.25 31C54.25 31.5139 54.0459 32.0067 53.6825 32.37C53.3192 32.7334 52.8264 32.9375 52.3125 32.9375ZM52.3125 3.875C50.7714 3.87654 49.2939 4.48942 48.2041 5.57914C47.1144 6.66887 46.5015 8.1464 46.5 9.6875C46.5066 10.6157 46.738 11.5284 47.1742 12.3477L39.9048 19.375H34.875V23.25H41.4702L49.9953 15.0118C50.7872 15.3571 51.6461 15.5215 52.5096 15.493C53.373 15.4644 54.2193 15.2438 54.9867 14.8469C55.7541 14.4501 56.4234 13.8872 56.9458 13.1991C57.4682 12.511 57.8306 11.715 58.0065 10.8692C58.1825 10.0234 58.1677 9.14899 57.9631 8.30963C57.7585 7.47027 57.3694 6.68709 56.8239 6.01711C56.2785 5.34712 55.5905 4.8072 54.8101 4.43664C54.0297 4.06608 53.1764 3.87421 52.3125 3.875ZM52.3125 11.625C51.9293 11.625 51.5547 11.5114 51.2361 11.2985C50.9175 11.0856 50.6691 10.783 50.5225 10.429C50.3758 10.0749 50.3375 9.68535 50.4122 9.30951C50.487 8.93368 50.6715 8.58845 50.9425 8.31748C51.2134 8.04652 51.5587 7.86199 51.9345 7.78723C52.3103 7.71247 52.6999 7.75084 53.0539 7.89749C53.408 8.04413 53.7106 8.29247 53.9235 8.61109C54.1364 8.92971 54.25 9.3043 54.25 9.6875C54.25 10.2014 54.0459 10.6942 53.6825 11.0575C53.3192 11.4209 52.8264 11.625 52.3125 11.625Z" fill="currentColor"/> <path d="M34.875 11.625H38.75V7.75H34.875C33.7709 7.75369 32.6804 7.99469 31.6775 8.45667C30.6747 8.91866 29.7829 9.59082 29.0625 10.4276C28.3421 9.59082 27.4503 8.91866 26.4475 8.45667C25.4446 7.99469 24.3541 7.75369 23.25 7.75H21.3125C16.6894 7.75513 12.257 9.59393 8.98799 12.863C5.71893 16.132 3.88013 20.5644 3.875 25.1875V36.8125C3.88013 41.4356 5.71893 45.868 8.98799 49.137C12.257 52.4061 16.6894 54.2449 21.3125 54.25H23.25C24.3541 54.2463 25.4446 54.0053 26.4475 53.5433C27.4503 53.0813 28.3421 52.4092 29.0625 51.5724C29.7829 52.4092 30.6747 53.0813 31.6775 53.5433C32.6804 54.0053 33.7709 54.2463 34.875 54.25H38.75V50.375H34.875C33.8476 50.374 32.8626 49.9654 32.1361 49.2389C31.4096 48.5124 31.001 47.5274 31 46.5V15.5C31.001 14.4726 31.4096 13.4876 32.1361 12.7611C32.8626 12.0346 33.8476 11.626 34.875 11.625ZM23.25 50.375H21.3125C18.0545 50.3692 14.9073 49.1916 12.4457 47.0572C9.9841 44.9229 8.37242 41.9743 7.905 38.75H11.625V34.875H7.75V27.125H13.5625C15.1036 27.1235 16.5811 26.5106 17.6709 25.4209C18.7606 24.3311 19.3735 22.8536 19.375 21.3125V17.4375H15.5V21.3125C15.5 21.8264 15.2959 22.3192 14.9325 22.6825C14.5692 23.0459 14.0764 23.25 13.5625 23.25H7.905C8.37242 20.0257 9.9841 17.0771 12.4457 14.9428C14.9073 12.8084 18.0545 11.6308 21.3125 11.625H23.25C24.2774 11.626 25.2624 12.0346 25.9889 12.7611C26.7154 13.4876 27.124 14.4726 27.125 15.5V23.25H23.25V27.125H27.125V34.875H23.25C21.7089 34.8765 20.2314 35.4894 19.1416 36.5791C18.0519 37.6689 17.439 39.1464 17.4375 40.6875V44.5625H21.3125V40.6875C21.3125 40.1736 21.5166 39.6808 21.88 39.3175C22.2433 38.9541 22.7361 38.75 23.25 38.75H27.125V46.5C27.124 47.5274 26.7154 48.5124 25.9889 49.2389C25.2624 49.9654 24.2774 50.374 23.25 50.375Z" fill="currentColor"/> </g> <defs> <clipPath id="clip0_5994_7571"> <rect width="62" height="62" fill="currentColor"/> </clipPath> </defs> </svg>

Machine Learning

Not a gimmick, but real added value

Follow us on LinkedIn

Stay up to date on the exciting world of data and our team on LinkedIn.

Follow on LinkedIn
Abstrakter Pfad des Data Institutes