ARGUS and Voyanta are now a part of Altus Analytics

BUSINESS NEEDS FOR A FAST DATA STRATEGYGordon Griffin, Chief Architect,

October 2017

ARGUS and Voyanta are now a part of

ABOUT VOYANTA

argussoftware.com | voyanta.com 2

Founded

2012

Launched

2013

Cloud-based

SaaS

Platform

London HQ

New York

Office

Subsidiary of The

Altus Group

Sister company

of ARGUS

Software

ARGUS and Voyanta are now a part of

WHO WE SERVE

3

The World’s Leading Real Estate Companies Use Voyanta

ARGUS and Voyanta are now a part of

WHAT VOYANTA DOES

4

XML

</>

CSV

Abc,

123,

XLSX

Data Quality Filters

Multiple File Formats

???User

AutomationFTP Upload

File Upload

Input Form

APIs

FTP Export

Data Gathering and

Validation

Data Repository BI and Data

Export

APIs

ARGUS and Voyanta are now a part of

BI DATA MODELLING – CHALLENGES

5

Challenge Original solution

• Broad, complex relational data source

• Transform to numerous complex, tightly specified

reports and dashboards.

• Complex, fine grained permissions model

• Huge cube-type in memory models

• development complexity,

• scaling and performance issues

• Reuse of & access to data model • All in one data model and visualisation solution

• No ability to expose the data model to other uses

(APIs)

• Can’t pull in data from outside the model

• Minimise time from data in to report

availability

• Massive investment in data refresh/reload, auto

scaling infrastructure and queues.

• Customers still waiting over 1 hour for report

refresh.

• Fast, responsive UI & Visualisations:

Minimise time from Click to Presentation.

• In memory cube excels in this area.

ARGUS and Voyanta are now a part of

NEW ARCHITECTURE - VISION• 3 tier modular architecture:

• Database

• Data Transform

• Visualisation

• Plug and play different data sources, visualisation tech

6

MySQLMySQL

MySQL

Java

REST

APIs

Data

Transform

BI

Visualisation

Javascript

Excel Add In

ARGUS and Voyanta are now a part of

MODULARITY & REUSE

• Views built on views

• “Facts” can be used as building blocks

• Code reuse

• Consistency

• Compliance

• Separate data transform from

Visualisation

7

Source Tables

Endpoints

(Reports)

Base Views

(facts)

Visualisations

ARGUS and Voyanta are now a part of

DATA TRANSFORMATION

• Create a transformed copy of data

• Require batch builds

• PRO: Rapid queries on pre-built views

• CON: Delay between data in and data

availability

• Mitigate with:

• Incremental builds

• Management of build triggers

• =>Complexity

8

• “ETL On Demand”

• Create Virtual databases, implementing

data transformations

• PRO: Instant availability of data

• CON: complex views on data sources

can be too slow for interactive users

• Mitigate with:

• Partial caching

• Full caching

• => ETL

DATA VIRTUALISATIONETL/CUBE

ARGUS and Voyanta are now a part of

THE “FAST DATA” TRADE-OFF

• Fast UI

• Pre-build ETL or Cube

• Build the answer to all

possible questions

• Hours to build a cube

9

• Fast Data Availability

• Render BI from raw data

• Pull data from the source

without delay

• 30 seconds to render a

dashboard from raw data

VS

ARGUS and Voyanta are now a part of

CACHING IN DATA VIRTUALISATION

• Full Cache

• Built in advance (overnight)

• c.f. ETL

• Data Lag

10

• No Caching

• For simpler/low volume

transformations

• “Time to Live” partial cache

• Simple to implement

• “Cold cache” and cache misses

• Data lag

• “Invalidate and re-query” partial

cache

• Minimise (not eliminate) cold cache

• Requires closer integration

ARGUS and Voyanta are now a part of

“FAST DATA” HEATING

11

Storage Speed

Hadoop,

MapReduce

Cold

In Memory Data

Hot

“Simple” Data

Virtualisation

Partial Caching

Full Caching

Base View ETL

Post DV Extract

Data Delivery

ResponseEmailed

reports

Cold

Customer

Dashboards

Hot

Data

Exploration

Heating requires

• Energy

• Time

ARGUS and Voyanta are now a part of Altus Analytics

BUSINESS NEEDS FOR A FAST DATA STRATEGYGordon Griffin, Chief Architect,

October 2017