This document provides an agenda and overview for a LoQutus Analytics & Insights event. The agenda includes introductions, presentations on scaling analytics with Microsoft, data-driven applications with R Shiny, and a networking drink reception. Presentations will cover LoQutus services, the analytics value chain, data focus components and services, data lakes vs data warehouses, self-service data experiences, and the Microsoft cloud data platform. The R Shiny presentation will discuss building interactive data apps in R.

1. LoQutus Analytics & Insights

2. Thomas Michem
Welcome

3. Ruben
Van den broecke
Next Up
Stijn
Vannieuwenborgh

4. Agenda
LoQutus
Intro
Scaling Analytics
With
Microsoft
Data Driven Apps
R Shiny Deepdive
Network Drink
18u15 18u30 19u10 19u40
10 Minutes

5. LoQutus and the Digital Age

6. DIGITAL
How can I benefit from
digital transformation
ARCHITECT
Data-driven (re)design of
your IT landscape
INTEGRATION
Integrate your systems in a
meaningful way
ANALYTICS
How to gain insights from
your data

7. The Art of Innovation
Jumping
to the next level
of Analytics & Insights
Guy Kawasaki

8. The Surprisingly Cool History of Ice
Guy Kawasaki
Bigger Blocks
Bigger Saw
Faster horses
“Artificial” Ice

9. AnalyticsValue Chain
WHAT HAPPENED?
Descriptive Analytics
WHY DID IT HAPPEN?
Diagnostic Analytics
WHAT WILL HAPPEN?
Predictive Analytics
HOW CAN WE MAKE IT
HAPPEN?
Prescriptive Analytics
Data
Stories
Dashboards
Reports
Visuals
Analytic
Models
Data
Driven
Apps

10. Analysis Layer
Developing analysis models, algorithms and calculations in order to
visualize, analyze, forecast, simulate what-if scenario’s with data.
Data Layer
Bringing together disparate data sources, building robust data pipelines
for data cleaning, transformation, aggregation. Preparing data for analysis.
Insights Layer
Innovation with data. Testing new ideas in an innovation lab to
produce and deploy analytic models to improve your bottom line.
Machine Learning Models
Dashboards
Shared Reports
Architecture & Governance
Advanced Data Analysis
Modern Data Engineering
How we help organizations solve ‘the puzzle’
Our aim = leverage your data to support your goals

11. Model
Building
Expert
Evaluation
Data
Understanding
Business
Understanding
Data
Preparation
Deliver
Insights
01 02
03
0405
06Better Business Questions
Data Model
ETL / Feature Engineering
Model Selection and Evaluation
Feedback with stakeholders
Deploy, Publish, Share
Qrisp BIBased on CRISP-DM
Cross-Industry Standard for Data Mining

12. The Data DrivenVision

13. Data Focus - Components
Business
Outcomes
Data
Products
Data Layer
Relevant
Data
Sources
Data
Warehouse
Operational
Data Store
Data
Mart
Data Lake

14. Data Focus - Services
Business
Outcomes
Data
Products
Data Layer
Relevant
Data
Sources
Data
Quality
Metadata
& Data
Lineage
Data
Preparation
Security
Governance

15. Data Lake or DataWarehouse?

16. The full Data Hierarchy
Analytical Data
Master Data
Reference & Metadata
Transactional Data
Streaming Data
ANALYTICAL DATA
KPI’s, Aggregated data, enriched data
MASTER DATA
Clients, Products, Enterprise Structure, ..
REFERENCE & META DATA
Classification schemas, external data and data about data
TRANSACTIONAL DATA
Records describing key agreements with your customers
STREAMING DATA
All measureable interactions with clients, employees and assets

17. Self-service data experience
Data Platform
It just works!
Everything is
connected
It is up to date
It’s top quality &
ready to use
Data Products
Business Outcomes

18. Data Platform
Ingest GovernanceData
Sources Streaming
Serving
Storage
Batch
Logs (unstructured)
Media (unstructured)
Files (unstructured)
Business/custom apps
(structured)
Dashboards
Key views on data,
visualizing KPI’s, evolution
and patterns
Analytic Models
Advanced analytics
automating decisons,
pattern recognition,
recommendations, …
Data Driven Apps
Environment to interactively
query, visualize & interact
with data

19. LoQutus and Microsoft Platform

22. What to do with these trends?
https://www.linkedin.com/pulse/why-trends-you-ride-biggest-choices-strategy-chris-bradley/

23. Tactic 1 –Try to find the best tool

24. Tactic 2 – Leverage building blocks

25. Data Infrastructure & Analytics

26. Azure Data Components
• https://azureinteractives.azurewebsites.net/
• https://azureinteractives.azurewebsites.net/Azure101Cards/default.html

27. The Data DrivenVision

28. Microsoft Cloud Data Platform

29. DataVisualisation + Data Services

30. Data visualization tools
Data
Apps
R Shiny, Dash,
Web
Apps
Angular, D3, …
BI-tool
Embedded mode
BI-tool
Publish mode
Frequency of changes
of visualisations
Number
of users

31. Microsoft Self-Service Stack
SSAS TABULAR
05

32. Excel Optimisation
Excel core
arithmetic
Advanced
Excel,
vlookups,
pivots
Power
Query,
PowerPivot
/ DAX
Optimised
data layer +
PowerPivot
Capabilities
Expertise

33. DataTransformation in Excel

34. Power Query –Transformation Recipe

35. Where to find Power Query

36. =

37. Aren’t you tired of this?

38. DAX - DATA ANALYSIS EXPRESSION
LANGUAGE
https://community.powerbi.com/t5/Data-Stories-Gallery/DAX-Reference-Cheat-Sheet/td-p/483212

39. Power Pivot

40. The POWER OF DASHBOARDS
BI

41. OPERATIONAL
TACTICAL
STRATEGIC
Mission Performance Goals
..
.
Progress Status Priority
..
.
Monitoring Quality Issue
..
.
http://www.loqutus.com/content/dashboarding-not-tool
Dashboarding is not a tool!

42. Correlation
Evolution
Comparison
Detail
KPIs
Geospatial
VISUALS

43. CLEAN DATA = EDIT QUERIESCLEAN DATA = EDIT QUERIES

44. BECOME A
POWER BI
GURU
IN X DAYS

45. What is (Azure) Analysis Services
• Semantic data model
• In-Memory storage
• Fast data query
https://docs.microsoft.com/en-us/azure/analysis-services/analysis-services-overview

46. SSAS Semantic Model

47. Same engine as Power BI / Power Pivot!

48. 48
Analytics & Insights voor Gent Levert
Kunnen we via
een duidelijk, helder visueel rapport
inzicht krijgen
in de stadsdistributie leveringen
om voortgang te monitoren en bijsturing te
definieren?
Initieel dashboard met
inzichten leveringen
Validatie met
stakeholders
Uitwerken van piloot

49. Stad Gent Levert

50. Revenue SimulationTool
Excel
Power QueryPower Pivot
Using a familiar end
user tool
Enriched with
’power’-full features
On data optimized for
analytics & insights SSAS Tabular Model
SSIS Extract, Transform, Load
6 billion rows
5 million rows
Simulation
Results

51. Extended CORE
Ingest Governance
Arcelor Mittal Data Lake Study + POC
Data
Products
Other
Relevant
Data
Sources
Streaming
Serving
Storage
Batch
Standard
CORE
Custom
Apps
Data
Integration

52. Microsoft Self-Service Stack
SSAS TABULAR
05

53. Short Break
10 Minutes

54. LoQutus and Open Source – R Shiny Data Driven Apps

55. Ruben
Van den broecke
Data Driven Apps
Stijn
Vannieuwenborgh

56. The Power of R
• Open source
• Statistical computing and data-analysis
• User-created Packages
• Active Community
• Facebook, Google, ... use it. And you?

57. Data Apps
Data
Apps
R Shiny, Dash,
Web
Apps
Angular, D3, …
BI-tool
Embedded mode
BI-tool
Publish mode
Frequency of changes
of visualisations
Number
of users

58. Shiny Data Analyst /
Scientist
Web developer /
BI expert
• Interact. Analyze. Communicate.
• Computational power of R
• Interactivity of the modern web

59. Building Blocks
12.500 & counting

60. QRISP Methodology
caret

61. Out of the Box Templates

62. Interactivity options

63. Deployment: ShinyProxy
Shiny App
Shiny App
...End-Users Data Developers
• easy deployment
• secure access (SSO, RBA)
• open source

64. Healthcare Analytics
Optimizing capacity through the healthcare value chain

65. Healthcare Analytics
Optimizing capacity through the healthcare value chain

66. Healthcare Analytics
Optimizing capacity through the healthcare value chain

67. Platform Simulation
Simulate collaboration between 22+ hospitals

68. Platform Simulation
Simulate collaboration between 22+ hospitals

69. Predictive Modeling
Based upon historical patterns in you data, predict a specific outcome

70. Network Drinks