Hyperight

Can You Build AI With Ever Increasing Fragments of Data Stores? – Kyosti Laiho

Building and using Artificial Intelligence and advanced analytics is gaining momentum, for relatively obvious reasons. As usual with any new data processing systems, it needs to build on data that is relevant for the purpose. At the same time, organizations keep struggling with managing the legacy – increasing set of old and new application databases, various data models, number of data marts and warehouses, big data evolution and use of increasing amount of open source solutions. At the same time, the users of these systems seem to asking for simple Excel sheets and self-service access to build their own views, to cope with their daily work, on top of everything else. So, where is the relevant data for AI and advanced analytics, how fragmented is it? What kind of data architecture and policies supports you the best – should it be controlled centralized data, a laissez faire approach, or a managed combination of both?

Add comment

Highlight option

Turn on the "highlight" option for any widget, to get an alternative styling like this. You can change the colors for highlighted widgets in the theme options. See more examples below.

Instagram

Instagram has returned empty data. Please authorize your Instagram account in the plugin settings .

Ivana Kotorchevikj

Categories count color

Advertisement

Small ads

Flickr

  • Traffic lights
  • WoMo
  • Setra presentation
  • It never ends
  • stand still screening-smoking girl
  • Maria d'Odessa performs her art of make-up
  • Afro-deko-mono
  • Maria d'Odessa, touching
  • Maria d'Odessa au bâton de rouge-baiser

Social Widget

Collaboratively harness market-driven processes whereas resource-leveling internal or "organic" sources.

ThemeForest