Innovation Guide

Transforming IT systems into agile data hubs

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A guide on how to bring more innovation into existing IT services.

From the author:

If you have ever wondered how it is possible to manage complex IT premises and still be open for innovation, use of new technologies, and don’t suffer from the maintenance burden this material is for you. You will learn how to build and operate a system that leverages standardised data flows inits processes and understand how to avoid creating siloed ecosystems that are unable to benefit from other data sources, nor can deliver meaningful data to other partners.

Table of contents:

  • Risks of siloed systems
  • Documenting data life-cycle
    in agile IT services
  • Easing out innovation costs
    with simple 3-steps methodology
  • Data types & data extraction technologies/services
  • Transparent and automated data flows
  • Effective data distribution framework & possible uses
  • Security, performance and maintenance challenges you may face (with solutions)

Krzysztof Szromek

Chief Technology Officer

Why should you bother? What will you learn?

Data Flows

Machine Learning

C4 Model

API

Ease out innovation costs by sharing data across services.

Extracting data
from media files.

Describe architecture at four different levels of granularity.

Learn about available technologies & how to design effective API architecture.

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