~ Self Service Data Components ~

Sanja Plohl
BI Developer & Analyst
Jose Farfan
Head of BI

What we do?

About

  • founded 2013 in Gibraltar

  • profitable since day 1 without recourse to external funding

  • now over 7 million customers and over 300 employees spread across 11 offices around the world

 

About

Award-winning on a global scale

Big Data is used to enhance customer experience

  1. Understand the value of each customer
  2. Predict likelihood of churn
  3. Develop personalised retention strategies

Reporting with Microstrategy

Integration in the pipeline

Scratchcards

BI System

BI 2015

Batch processing

BI 2017

Streaming

Specific models for:

Who needs the data:

- Country Managers
- Senior Managers
- Dev teams


- Marketing
- B2B
- Finances
- Customer Services
- Fraud

BI 2019

Real-Time

processing

Publishing the information

Backed
Developers


BI
Admins

 

Business
Analysts


BI
Analysts

 

GAP
Product
Owners



Managers

 

Finance
 

Business
Experts
Data
Knowledge
High Technical skills
High Functional skills

BI Challenges

1. Constantly Changing Systems
2. Small team
3. A lot of requests

Data Discovery

Data Preparation

 

 

 

Visual Analysis

 

 

 

Review & understand the results

BI
Analyst

Business

Expert

What do we do now?

1. Deploy "standard" KPI reports

2. Organise Microstrategy training sessions

 

But this is not enough...

 

LL Data Server - BI Admin

  1. Configure data sources
  2. Define SQL
  3. Cache the information
  4. Update periodically

We use the capacity of Microstrategy to get the data from API rest source.

LL Data Server

BI Admin - Demo

That's All Folks!

Thank you for you attention.

Questions?

sanja.plohl@lottoland.com
jose.farfan@lottoland.com

www.lottoland.com

www.lottolandcorporate.com

LL Data Server Architecture

Data sources

LL Data Server

(our)

Front End Tool

(Angular 2)
BI Analysts,
Advance users
Business Analysts,
End users
Accesed by JDBC
Data Server API REST based on AKKA, cache the data and refreshes it periodically

Server Data Design

TARGETS:
  • Easy to use and extend
  • Performance
  • Scalablility
TECNOLOGIES:
  • AKKA Http
  • AKKA Actrors
  • APIREST
  • Scala
PROCESSES:
  • Definition data (one process to manage all definitions)
  • Scheduling (update and refresh)
  • Connectors server (manage the creation and manipulation of data) - JDBC, http rest, specific design,...
  • Data cache (serve the data and save in local filesystem and memory)
FUTURE:
  • Extend to other sources, such as Druid, ES,...
  • Publish on Github
  • Extend with Calcite
  • Scala
API REST Service
Data Cache
Data Definition

Scheduling
Connectors

Manage queries and system definitions

Queries

Queries

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