Assignment Sample on Data Driven Decisions for Business

1. Key challenges and trends that is increasing importance of data analysis

Now a day the data analysis is important for every business process without the data analysis the future analysis can not be easily done according to the scenario for various process. the technology is fast changing the business strategy according to the different kind of mapping based on the different kind of analysis. The main trends that is increasing the importance of data analysis huge volume of data that today all the process is executed in the digital based communication that is analysed in the proper manner and then the decision making process is need to be implement.

  • Better targeting
  • Know the target customers
  • New innovation
  • Cost cut analysis

Like that it is make it as the trend and also while using the data analysis there are many key challenges are there. The main challenge is to manage the different kind of data for the analysis the process according to the specification process and multiplication according to the system. Then considered with the huge volume of data that is implemented in the process of analysis based on the measurement. Like that it is focus on the different kind of attributes according to the scenario.

The following trends is needs to utilize the data analysis in the business.

  • Smarter and faster and creating the more responsible AI
  • Decision is taken based on the intelligence-based process according to this it is implemented.
  • X number of analytics can be done for this kind of applications
  • Augmented Data management

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Based on this the data analytics is play the important role business scenarios.

2. Summary Table

The summary table of the scenario that the bangles include with the functional and non-functional data is included in the table like that.

MARKET Year  

Customer

Month Category Sales Volume Sales Value Profit

Like that the summary table along with the bangles inclusion it is having the above-mentioned information. Like that it is focus on the different kind of data that is mapped into the selective information according to the scenario. For example, the following data is considered with the following measurement data.

  • Invoice number
  • Customer name
  • Year/ month
  • Category
  • Sales rate
  • Sales volume
  • Customer opinion

Like that it is need to considered with the different kind of process and different kind of data is need to be maintained for the various analysis according to different process. the functional and non-functional data is considered with the using the numerical and non-numerical data according to the functionality and process measurement of the analysis. Like that it is noticed into the analysis of the data according to the scenario. It is non numerical means then it is containing the information of every analysis according to the process and communication of different aspect of analysis based on the measurement. It may be different in each scenario. The data set is playing the important of the data analysis process.

3.Highlights of issues in the data

There is no big issue in the data because it is focus on the numerical data value only according to that the process is considered with the adding the new category of data that is bangles into the group that is need to considered in the analysis according to the different kind of scenario based on the mapping system for the analysis.

  • The main issue if we added the value into the existing data set means it is need to have the adoptable facility based on the analysis of each process.
  • Like that it is notice with the specific functionality according to the data type.
  • Some of unrelated data can be related to the facility of process according to each process and analysis.

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The process according to the different kind of measurement based on the analysis is considered with the development for the utilization and process according to the services.

4. Statistics Creation

  1. Total volume and sales value by month
Month Sum of Sales Volume Sum of Sales Value
1 970 1091621.96
2 1135 1329471.54
3 862 942370.8
4 661 754331.24
5 985 1139144.28
6 1281 1504904.76
7 1060 1188059.98
8 905 1017553.01
9 1070 1180023.51
10 700 746992.69
11 814 889228.16
12 877 952390.54
Grand Total 11320 12736092.47

  1. Average prices per month by category and total
Month Accessory Ankle bracelet Bracelet Hair band Hairband Necklace Ring Grand Total
1 6122.33 410211.75 284250 301015.15 90022.73 1091621.96
2 62665.24 502853.6 324860.29 333205.27 105887.14 1329471.54
3 32092.94 414381.46 216910.07 221421.96 57564.37 942370.8
4 26594.68 2500 335726.7 167105.49 163155.93 59248.44 754331.24
5 47912.44 420252.34 328052.59 251077.64 91849.27 1139144.28
6 85289.47 599339.07 348994.08 375455.05 95827.09 1504904.76
7 67483.84 526508.83 205625.52 296566.57 91875.22 1188059.98
8 39170.48 436451.5 221599.89 28858.92 229578.36 61893.86 1017553.01
9 74583.63 558133.54 167406.78 73150.49 196543.4 110205.67 1180023.51
10 38795.08 328844.28 183371.07 59662.3 93773.61 42546.35 746992.69
11 35959.98 386457.65 184379 32922.49 186237.49 63271.55 889228.16
12 7480.74 395607.41 273347.45 183799.94 92155 952390.54
Grand Total 524150.85 2500 5314768.13 2905902.23 194594.2 2831830.37 962346.69 12736092.47

  1. Total volume and sales by category and total by year and by quarter
  2. Year on year volume, sales value and average price by category and total

5. Statistics

  1. Total volume and sales value by month
  2. Average prices per month by category and total
  3. Total volume and sales by category and total by year and by quarter
  4. Year on year volume, sales value and average price by category and total

6. Chart explanation

The above chart is having the value of sales and sales amount based different category according to the year and months. The average of the sales is mapped into the year and month of the process. then it is considered various category analysis in this bracelet is highly sailed that is predicted using the data analysis. Like that the visualization provide useful information for taking the future based decision making process according to that it is predicted and applied into the feature based analysis.

This is useful for which is category is mostly like by the customer and how can we increase the product for the increasing the profit of the organization like that it is mapped based on the value.

References

EMC, 2018. Data Science Revealed: A Data-Driven Glimpse into the Burgeoning New Field. Retrieved from the World Wide Web. The Fourth Paradigm: Data-Intensive Scientic Discovery. Microsoft, pp. 2-9.

Gleichauf, S. A. a. B., 2019. Application of Enterprise Models for Engineering Enterprise Transformation. Enterprise Modelling and Information Systems Architectures, 5(1), pp. 59-63.

Hayashi, C., 2017. What is Data Science? Fundamental Concepts and a Heuristic Example. In Proceedings of the 5th Conference of the International Federation of Classication Societies (IFCS’96), pp. 2-14.

Weske, M. M. I. W. a. J. v. B., 2018. Business Process Management Forum:. BPM Forum 2018, Sydney, NSW, Australia Switzerland: Springer, 2(2), pp. 23- 29.

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