Please Using Description Develop Data Flow Diagram Dfd Picture Task Given Don T Professio Q43825174
Please using description below develop Data flowdiagram(DFD). On the picture task is given. Don`t have to beprofessional model.
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For most businesses and government agencies, lack of data isn’ta problem. In fact, it’s the opposite: there’s often too muchinformation available to make a clear decision.
With so much data to sort through, you need something more fromyour data:
- You need to know it is the right data for answering yourquestion;
- You need to draw accurate conclusions from that data; and
- You need data that informs your decision making process
In short, you need better data analysis. With the right dataanalysis process and tools, what was once an overwhelming volume ofdisparate information becomes a simple, clear decision point.
To improve your data analysis skills and simplify yourdecisions, execute these five steps in your data analysisprocess:
Step 1: Define Your Questions
In your organizational or business data analysis, you must beginwith the right question(s). Questions should be measurable, clearand concise. Design your questions to either qualify or disqualifypotential solutions to your specific problem or opportunity.
For example, start with a clearly defined problem: A governmentcontractor is experiencing rising costs and is no longer able tosubmit competitive contract proposals. One of many questions tosolve this business problem might include: Can the company reduceits staff without compromising quality?
Step 2: Set Clear Measurement Priorities
This step breaks down into two sub-steps: A) Decide what tomeasure, and B) Decide how to measure it.
A) Decide What To Measure
Using the government contractor example, consider what kind ofdata you’d need to answer your key question. In this case, you’dneed to know the number and cost of current staff and thepercentage of time they spend on necessary business functions. Inanswering this question, you likely need to answer manysub-questions (e.g., Are staff currently under-utilized? If so,what process improvements would help?). Finally, in your decisionon what to measure, be sure to include any reasonable objectionsany stakeholders might have (e.g., If staff are reduced, how wouldthe company respond to surges in demand?).
B) Decide How To Measure It
Thinking about how you measure your data is just as important,especially before the data collection phase, because your measuringprocess either backs up or discredits your analysis later on. Keyquestions to ask for this step include:
- What is your time frame? (e.g., annual versus quarterlycosts)
- What is your unit of measure? (e.g., USD versus Euro)
- What factors should be included? (e.g., just annual salaryversus annual salary plus cost of staff benefits)
Step 3: Collect Data
With your question clearly defined and your measurementpriorities set, now it’s time to collect your data. As you collectand organize your data, remember to keep these important points inmind:
- Before you collect new data, determine what information couldbe collected from existing databases or sources on hand. Collectthis data first.
- Determine a file storing and naming system ahead of time tohelp all tasked team members collaborate. This process saves timeand prevents team members from collecting the same informationtwice.
- If you need to gather data via observation or interviews, thendevelop an interview template ahead of time to ensure consistencyand save time.
- Keep your collected data organized in a log with collectiondates and add any source notes as you go (including any datanormalization performed). This practice validates your conclusionsdown the road.
Step 4: Analyze Data
After you’ve collected the right data to answer your questionfrom Step 1, it’s time for deeper data analysis. Begin bymanipulating your data in a number of different ways, such asplotting it out and finding correlations or by creating a pivottable in Excel. A pivot table lets you sort and filter data bydifferent variables and lets you calculate the mean, maximum,minimum and standard deviation of your data – JUST BE SURE TO AVOIDTHESE FIVE PITFALLS OF STATISTICAL DATA ANALYSIS.
As you manipulate data, you may find you have the exact data youneed, but more likely, you might need to revise your originalquestion or collect more data. Either way, this initial analysis oftrends, correlations, variations and outliers helps you FOCUS YOURDATA ANALYSIS ON BETTER ANSWERING YOUR QUESTION and any objectionsothers might have.
During this step, data analysis tools and software are extremelyhelpful. Visio, Minitab and Stata are all good software packagesfor advanced statistical data analysis. However, in most cases,nothing quite compares to Microsoft Excel in terms ofdecision-making tools. If you need a review or a primer on all thefunctions Excel accomplishes for your data analysis, we recommendthis HARVARD BUSINESS REVIEW CLASS.
Step 5: Interpret Results
After analyzing your data and possibly conducting furtherresearch, it’s finally time to interpret your results. As youinterpret your analysis, keep in mind that you cannot ever prove ahypothesis true: rather, you can only fail to reject thehypothesis. Meaning that no matter how much data you collect,chance could always interfere with your results.
As you interpret the results of your data, ask yourself thesekey questions:
- Does the data answer your original question? How?
- Does the data help you defend against any objections? How?
- Are there any limitation on your conclusions, any angles youhaven’t considered?
If your interpretation of the data holds up under all of thesequestions and considerations, then you likely have come to aproductive conclusion. The only remaining step is to use theresults of your data analysis process to decide your best course ofaction.
By following these five steps in your data analysis process, youmake better decisions for your business or government agencybecause your choices are backed by data that has been robustlycollected and analyzed. With practice, your data analysis getsfaster and more accurate – meaning you make better, more informeddecisions to run your organization most effectively.
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6. Develop 3 level data flow diagram (context level, 0-level, two 1st level diagrams). should the data flows shown between that be Remember transformations/processes/activities (not the units performing these functions)! Show transcribed image text 6. Develop 3 level data flow diagram (context level, 0-level, two 1st level diagrams). should the data flows shown between that be Remember transformations/processes/activities (not the units performing these functions)!
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