Data Marketing Management
My Boss told to me, he wants to make a central system what will be provide the data to sales when they make a presentation in meeting, follow up the customer, and give report to their boss.
My boss gives me two options:
- Create a new system and implement it to be an application, it can be access using mobile phone and desktop.
- Create a new data lake, the sales can request the data what they want, and the engineer call the data as the request.
The boss gives me Data Marketing Management Schema:
My boss wants all of object in that schema (Regiograph, Datapool, Hootsuite, Facebook, Linkedin, Youtube, etc) can be in one source and the sales can connected to them in “one gate”.
I leave my boss room, take a glass of coffee and see the schema. Let’s start to analysis the schema!
Analysis:
Based on project management triangle, the project quality will depend on this parameter:
- Time (schedule).
- Cost (budget).
- Scope / requirements (totality of work or scope).
One of the three sides of the triangle will be the primary project driver the one variable to which the other variables will be subordinated or sacrificed.
Time, the boss does not give a strict timeline, so the timeline can be sacrificed.
Cost, the boss just gives the assignment, he does not give some advice about what tools will be used and not do budgeting allocate for feature and tools. Using free tools as his expected.
Scope/Requirements, Because of the tight cost, the feature will be in not best provision. So, it will be dependent with cost.
Based on diagram, my boss give highlight in 4 points:
- Data Pool, that’s a bunch of data what collected with sales using social media, visit to client and internet.
- Social Media Tool, that’s any tools about social media what used with sales to get connected with prospect customer.
- Content Info, that’s any tools about conduct some content will be broadcast using Social Media tool and sales activity.
- Sales, that’s about activity to reach the prospect customer using direct meeting and CRM (Customer Relationship Management) tools.
Based on that’s point, I will be concluded, this company need an architecture system like Hadoop that facilitates using a network of many computers to solve problems involving massive amounts of data and computation.
Using Hadoop, the users can query the database in a centralized system, environment sharing and showing the diagram based on data. Based point of requirement, I will give insight about data distribution, data usage dan data storage in an environment:
- Data Pool -> Using MySQL to store the data. The user can query using Hue. If the user wants to get business insight, they can export the data and explore it using Python and scikit-learn.
2. Social Media -> The data on social media will be get using API (Application Programming Interface). If the API can’t provide the data, this company must hire the third party to get the data from social media activities.
3. Content Info -> The content info can store on Data Pool. The google docs and anything data composer tools will be migrated into Data pool and in next time, the data will store to Data Pool too. The software developer must create own internal file sharing system to provide the employee to store the file into Data Pool.
4. Sales -> The software engineer must create own CRM (Customer Relationship Management) and the data will be stored into Data Pool. The Sales who come to client must input the visited report in CRM.
Conclution :
The data will be stored in common storage (Data Pool), so the data will be centralized in one point. The data analyst or data scientist will be easy to get dataset in Data Pool. The management will get the best insight from their data crew.
Reference :
White, T. (2012). Hadoop — The Definitive Guide: Storage and Analysis at Internet Scale (4. ed., revised & updated).
G. M. Campbell, S. Baker, Project management. 4th edition. New York, NY: Alpha, 2007.
Mcghee, P., & Mcaliney, P. (2007). Painless Project Management: A Step-by-Step Guide for Planning, Executing, and Managing Projects.
