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What can you gain out of data analytics?
Value to your business and complexity of analytics
"Imagine your business unleashing the power of data"
4
prescriptive analytics
3
predictive analytics
2
diagnostic analytics
1
descriptive analytics
descriptive analytics
"What happened?"
diagnostic analytics
"Why did this happen?"
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Backward looking
+ Detects and describes patterns
+ Provides insights into the past and guides how to dig deeper
predictive analytics
"What is likely happen?"
prescriptive analytics
"What do we need to do?"
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Forward looking
+ Provides optimisation and decision rules (for future events based on probabilities)
+ Recommends one or more actions from prediction models
What are the steps to data analytics?
Step 1 & 2
Identify goals early to provide project with direction
Decide on objectives
Identify business levers
Optimise and repeat
1
2
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Data collection
3
Step 3
Get more data from diverse sources to find better correlations, build better models and find more actionable-insights
Data modelling
5
Data cleaning
4
Step 6
Data value chain is a repeatable process which leads to continuous improvement to the business and the data itself
Step 5
Models will be built to correlate data with business outcomes and make recommendations
Step 4
Clean data to prevent distortion of analysis. Clean data provides better outcomes.
Which data maturity level are you at right now?
Data analytics journey
No data, no decision.
maturity level 0
in the dark
We are OK, thanks
maturity level 1
catching up
Where do we start?
maturity level 2
first pilot(s)
How does this work?
Analytics seamlessly integrated into business processes.
maturity level 5
optimise and extend
Continue to learn and enhance
maturity level 4
strategic value
Current business is now dependent on big data
maturity level 3
tactical value
First project(s) show clear ROI
How we work with clients?
1
We recommend where to extract value through analytics.
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We scan external sources to find relevant available data to complement your data.
2
We extract data from your internal files and systems, and automate data cleaning where possible.
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We define trends and extract meaningful predictions through model and analytics.
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We recommend business and process improvements. We can build a dashboard to leverage data visualisation.
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We continuously monitor and bring insights from data analytics, and fine-tune the predictive models.
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