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We architect, not just for today, but for the future

From a traditional point of view, it may seem reasonable to keep tech/cloud agnostic approach and just follow the current need of our clients. But we think that it is more appropriate to think/walk with our clients and facilitate them for a more informed decision by promoting the outstanding moves of our partners. 

The Forrester Wave: Public Cloud Container Platforms, Q1 2022

“Google Cloud is the best fit for firms that want extensive cutting-edge cloud-native capabilities for distributed workloads spanning public cloud, private cloud, and multicloud environments.”

In this aspect, Google Cloud Platform (GCP) stands out for sure. As a premium partner of GCP, we are on cloud nine with their latest innovations, which are already acknowledged by the independent reports.

Unlock the full potential of Google Cloud Platform

We are aspired to usher you into the innovative google cloud ecosystem, a multi-tool for all your business needs.

It is impossible to cover all the offerings of GCP here. The best resource to refer for that is the official dedicated GCP Product web pages. Yet, we would like to highlight some of the latest developments which mitigates the concerns of EU governmental and non-governmental organizations such as data privacy, digital sovereignty, privacy and compliancy aspects. It is not surprising that Google produced the most comprehensive solutions such as Assured Workloads for EU,  Cloud External Key Manager (EKM) and Access Approval. We see those improvements as a further step in the development of a European Google Cloud.

Data Analytics Solutions of GCP

BigQuery: Serverless, highly scalable, and cost-effective multicloud data warehouse designed for business agility.

Looker: A modern business intelligence, embedded analytics, and data application platform

Dataproc: A fully managed and highly scalable service for running Apache Spark, Apache Flink, Presto, and 30+ open-source tools and frameworks for data lake modernization, ETL, and secure data science.

Dataflow: Unified stream and batch data processing that's serverless, fast, and cost-effective.

Pub/Sub: A messaging service that ingests events for streaming into BigQuery, data lakes or operational databases.

Cloud Data Fusion: Fully managed, cloud-native data integration at any scale for building and managing data pipelines.

Data Catalog: A fully managed and highly scalable data discovery and metadata management service.

Cloud Composer: A fully managed workflow orchestration service built on Apache Airflow.

Dataprep: An intelligent cloud data service to visually explore, clean, and prepare data for analysis and machine learning.

Dataplex: An intelligent data fabric that enables organizations to break free from data silos by empowering them to centrally manage, monitor, and govern their data across data lakes, data warehouses, and data marts with consistent controls, providing access to trusted data and powering analytics at scale.

Analytics Hub:  A data exchange service that allows you to efficiently and securely traffic data assets across organizations to address challenges of data reliability and cost.

Google Data Studio: An interactive data suite for dashboarding, reporting, and analytics.

Google Marketing Platform: A marketing platform that brings together your advertising and analytics to help you make quality customer connections, surface deeper insights, and drive better marketing results.

Database Solutions of GCP

Cloud Bigtable: Cloud-native wide-column database for large-scale, low-latency workloads.

Cloud Spanner: Cloud-native relational database with unlimited scale and 99.999% availability.

Cloud SQL: Fully managed database for MySQL, PostgreSQL, and SQL Server.

Firestore: Cloud-native document database for building rich mobile, web, and IoT apps.

Firebase: NoSQL database for storing and syncing data in real time.

Memorystore: In-memory database for managed Redis and Memcached.

Datastream: Serverless change data capture and replication service.

Database Migration Service: Serverless, minimal downtime migrations to Cloud SQL.

Prominent AI and Machine Learning Solutions of GCP

Vertex AI: Unified platform for training, hosting, and managing ML models.

Deep Learning VM Image: Preconfigured VMs for deep learning applications.

Vertex AI Workbench: A single interface for your data, analytics, and machine learning workflow.

Deep Learning ContainersPreconfigured and optimized containers for deep learning environments.

Vertex Data Labeling: Managed annotation for high-quality model training data.

TensorFlow Enterprise: Reliability and performance for AI apps with enterprise-grade support and managed services. 

AutoML: Custom machine learning model training and development.

Recommendations AI: Delivers highly personalized product recommendations at scale.

AI Infrastructure: Options for every business to train deep learning and ML models cost-effectively.

Container Solutions of GCP

Artifact Registry: Store, manage, and secure container images and language packages.

Cloud Build: Solution for running build steps in a Docker container.

Cloud Run: Fully managed environment for running containerized apps.

Container Registry: Registry for storing, managing, and securing Docker images.

Container Security:  Container environment security for each stage of the life cycle.

Deep Learning Containers: Containers with data science frameworks, libraries, and tools.

Google Kubernetes Engine (GKE): Managed environment for running containerized apps.

Operation Solutions of GCP

Cloud Debugger: Real-time application state inspection and in-production debugging.

Cloud Logging: Google Cloud audit, platform, and application logs management.

Cloud Monitoring: Infrastructure and application health with rich metrics.

Cloud Profiler: CPU and heap profiler for analyzing application performance.

Cloud Trace:  Tracing system collecting latency data from applications.

Cloud Error Reporting:  Real time exception monitoring and alerting.

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Create impact with the right technology

Interested in one or more of our used technologies? We are more than happy to explain the differences and how these technologies will create a data-driven impact.

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