This document discusses getting started with big data by presenting a simple approach. It recommends starting small with an isolated pilot project that delivers value fast by focusing on a realistic use case. The pilot should involve business users and not mystify big data. An example use case described is using predictive analytics on a telecom provider's infrastructure data to determine network expansion areas, outage probabilities, utilization levels, and more. Key aspects emphasized are starting eventually isolated, having a fast pilot setup, focusing on value first, using realistic cases, keeping the approach focused and clear, and involving the business.

1. Wir unternehmen IT.
Where are the users?
A (simple) story about getting
started with Big Data
Christian Löhnert
Big-Data-Meetup, Munich, 12.11.2015

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Do you know the Big Data BARC study?
17.11.2015 www.consol.de2
66 %
are not using
Big Data
less drivers
from
business departments

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obstacles

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approach

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start small, go fast
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take step
check
feedback
learn
start

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start - possible approach
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~week
analysis execution
common
potential
workshop analysis
specific
potential
pilot value iteration
~month

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example
telco provider

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data domains in a carrier infrastructure
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• Master Data
• Contracts & Lifecycle
• Orders & Provisioning
• Geo
• Numbers
• Equipment & Infrastructure
• Usage Data
• Detailed Provisioning Data
• Geo./ tech. availability
• Status & Health
• total revenue
• profit
• costs (network/ interconnect)
• manual credit notes
• dunning/ dept collection
• materials management
• Tickets & Service
• Mails
• Calls
• Social Media
• Clickstream
• Leads
• Campaigns
• Channels
• Internal/ interconnect/ reseller
• Phone, DSL, fiber, (mobile)
• Master Data

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customer/ contract life cycle
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Lead / Order
Customer/
Contract
Technical
Order/
Provisioning
Tech. Usage Billing
Issuing/
Dunning
Service
Next best Action
Targeting
Campaigns
Next best Action
Preventive Care
Churn Prevention
Predictive Infrastructure
Customer Segmentation Fraud Detection
Cross- /Up-Selling
Predictive Infrastructure

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Predictive Infrastructure – systems/ sources
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network
DSLAMs/ MDUs
end devices
CPEs
Configuration
systems
MonitoringProvisioning
Enterprise Datahub

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Predictive Infrastructure - questions
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Which network areas are suitable for
expansion?
Which outage probabilty of network
elements do we have? Why?
Where and when there are anomalous up-
and down-turns within the network?
Where and when is the network utilization
extraordinary high?
Where, when and how often there are
outages within the newtork?
Where and how does provisioning status
change?
What are the network parameters from end
device and network unit point of view?
complexity

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Predictive Infrastructure - usage
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• case related infrastructure information
service
• cluster and patterns of network behavior
• preventive maintanance
• network maps
infrastructure
• prediction of network utilization/ provisioning
network planning

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key aspects
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• eventually
isolated
• fast pilot
setup
• value first
• realistic use
cases
• focused
• do not
mystify
• involve
business
clear realistic
smallvalueable

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ConSol* Software GmbH
Christian Löhnert
christian.loehnert@consol.de
+49-89-45841-3169
...happy about any feedback 