The objective of hhis presentation is to present from data to better decision in the process of Analytics.

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From Data to better
Decision
Frehiwot Mulugeta
September 14, 2017
Data Analytics Specialist

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Outline
I. What is Data?
II. What is Analytics
 Advantages of Analytics
 Processes
 Types
 Method
 Developing Insight
III. Conclusion

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Data may be your most valuable resource.
 But it is more or less useless without analytics.
Analytics helps to discover meaningful trends.
What is Data?
Definition
facts generated from system or manual operations

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Some of HCMIS data are
Item Information :- Item Name, unit, Account, commodity
type, mode
Receive : Item name, quantity, unit cost, Amount
Distribution: issuer, receiver, Quantity distributed, amount
Financial: funding source, revenue, Amount of rdf & hpr
AND MORE
PFSA data sources are HCMIS system, Mbrana, I-import
What is Data . . .

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Analytics is multidimensional field
 that uses mathematics, statistics, predictive modeling
 to find meaningful patterns and knowledge in recorded
data.
What is Analytics?

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To visualize company performance
To see trends over time
It is a tool for business optimization
- Modify business process
To make data-driven & better decision
Advantages of Analytics
Analytics Improves data use & Fact based decision making.

7. Objective:
• Defining the objective
• Hypothesis
Data :
• Extraction, ensure high quality data,/Data cleaning/
Analysis:
• Develop Visualizations & Reports
• Developing actionable Insights
Insight:
• Interpret result
Reporting
• Disseminate result to support decision
Analytics Process

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Analytics Tools
Data Extraction
& Preparation
SQL
Excel
Tableau
Analysis
Tableau
Power Bi
Excel
Reporting
Tableau
dashboard
Infographics

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Data preparation
manipulation of data into a form suitable for analysis
 It is estimated that data preparation takes about 60%-80% of the
total time spent for data Analysis.
It is a process that involves many different tasks
Well prepared data will generate
informative insight

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Data Cleaning
Data cleaning is undertaken in order to improve the quality of data.
It involves with detecting & removing errors and inconsistencies/outliers/
from data
Data quality problems may occur at the time of data entry, trans
Good Data Quality leads to Better decision

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Data Quality
According to Research titled, “The State of Enterprise Data Quality: 2016;
Top 5 Causes of poor data quality are:-
Better Data Quality Accurate/better
Insight
Better decision

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1. Descriptive analytics
 What’s happening now?
 Techniques means and standard deviations
2. Diagnostics analytics
 why, and how a particular problem has occurred.
 correlation analysis, hypothesis test, analysis of variance
3. Predictive analytics - What is likely to happen next
-
Types of Analytics

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Descriptive mean, sum, …
 Comparison
 Bar charts
Changes over time/trend
 Line graphs
Aggregation
 Pie graphs
Relation ship/Correlation
 Scatter plots
Methods of Analysis

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Developing Insight
Document review
Internet review Googling
Discussing with Experts
Business Insights
Analysis of Result
Result Validation/
Triangulation

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 It should be aligned to the objective
 Propose recommendation
 Future analysis idea
Reporting Analysis of Result

16. Good Data
Quality
Sound
Analytics
Better
Decision
Organizational
Success
Conclusion

17. Reference
 https://www.sas.com/en_us/insights/analytics/what-is-analytics.html
 http://www.genpact.com/docs/resource-/data-to-insight-to-action-taking-
a-business-process-view-for-analytics-to-deliver-real-business-impact
 http://info.localytics.com/blog/difference-between-data-analytics-insights
 http://www.datapreparator.com/what_is_data_preparation.html
 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1198040/figure/pmed-
0020267-g001/
 http://www.blazent.com/top-5-causes-poor-data-quality/

18. Thank you