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a methodology to ensure eventual success in passion projects.

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PassionProj.md

@@ -28,6 +28,8 @@ thing your app holds for a User?
28 28 - add all your docs in a `doc/` folder
29 29 - draft initial README.md with summarized paragraph of the one-pager
30 30 - create a `src/` folder for all your source code
31 + - submit the Repo URL to the portal
32 +
31 33
32 34 ### Create all three tiers
33 35

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PassionProj.md

@@ -47,6 +47,8 @@ thing your app holds for a User?
47 47 - Load some User test data into the db behind the REST server with a SQL file.
48 48 - Prove data is loaded with SQL using an INNER join.
49 49 - Prove data is loaded with a tool like Postman
50 + - choices Spring, Django, or Flask (but the REST aspect of one of these)
51 +
50 52
51 53 ### VanillaJS Interface
52 54

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PassionProj.md

@@ -77,10 +77,8 @@ thing your app holds for a User?
77 77 - display `Piro`s by `User` and by `Tag`
78 78 - adding and removing of tags from a `Piro`
79 79
80 - **Getting fancy...**
81 80
82 -
83 - ### Add ReactJS UI
81 + ### Getting fancy... Add ReactJS UI
84 82
85 83 - add a reactjs interface that mimics your VanillaJS interface
86 84 - style it consistently

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PassionProj.md

@@ -77,7 +77,7 @@ thing your app holds for a User?
77 77 - display `Piro`s by `User` and by `Tag`
78 78 - adding and removing of tags from a `Piro`
79 79
80 - **Getting fancy...*
80 + **Getting fancy...**
81 81
82 82
83 83 ### Add ReactJS UI

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PassionProj.md

@@ -77,6 +77,9 @@ thing your app holds for a User?
77 77 - display `Piro`s by `User` and by `Tag`
78 78 - adding and removing of tags from a `Piro`
79 79
80 + **Getting fancy...*
81 +
82 +
80 83 ### Add ReactJS UI
81 84
82 85 - add a reactjs interface that mimics your VanillaJS interface

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1 file changed, 9 insertions

PassionProj.md

@@ -29,6 +29,15 @@ thing your app holds for a User?
29 29 - draft initial README.md with summarized paragraph of the one-pager
30 30 - create a `src/` folder for all your source code
31 31
32 + ### Create all three tiers
33 +
34 + - create frontend, business logic server, database backend
35 + - the goal of these first phases to get
36 + - something into a database
37 + - something from the database onto a web page
38 + - restrict the display of items based on ownership of user
39 + - something which can be added to db from the frontend based on the user
40 +
32 41 ### REST Server (initial)
33 42 - Build a small, single entity (`Entity-1`) rest server.
34 43 - Load some test data into the db behind the REST server with a SQL file for Entity-1.

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PassionProj.md

@@ -11,16 +11,18 @@ a Data Pipeline Application.
11 11
12 12 The one-pager, the UX/UI mocks, and the data model documents should be complete.
13 13
14 - Now, **What is your `Entity-1`??**
15 -
16 - In the Piro360 example, it is `Piro`
17 -
18 14 ## Method
19 15
20 16 Perform each of these phases in order.
21 17
22 18 ## 3-tier Web App
23 19
20 + Now, **What is your `Entity-1`??**
21 + In the Piro360 example, it is `Piro`
22 +
23 + You need to determine what entity you will focus one first, what is the key
24 + thing your app holds for a User?
25 +
24 26 ### Create Repo for Project
25 27
26 28 - add all your docs in a `doc/` folder

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PassionProj.md

@@ -1,7 +1,11 @@
1 1 # Outline line of Tasks
2 2 ZCW Passion Project methodology for PassionProj Week.
3 3
4 - Each of these phases are designed to move the project from the One-Pager stage to *something* working by the end of the week.
4 + Each of these phases are designed to move the project from the One-Pager stage to *something*
5 + working by the end of the week.
6 +
7 + There are two possible templates here, one for a 3-tier Web Applicationa and one for the creation of
8 + a Data Pipeline Application.
5 9
6 10 ## Documentation
7 11

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PassionProj.md

@@ -17,7 +17,7 @@ Perform each of these phases in order.
17 17
18 18 ## 3-tier Web App
19 19
20 - ## Create Repo for Project
20 + ### Create Repo for Project
21 21
22 22 - add all your docs in a `doc/` folder
23 23 - draft initial README.md with summarized paragraph of the one-pager
@@ -86,7 +86,7 @@ Perform each of these phases in order.
86 86
87 87 This is a comprehensive project plan outline for your data engineering pipeline.
88 88
89 - ## Create Repo for Project
89 + ### Create Repo for Project
90 90
91 91 - add all your docs in a `doc/` folder
92 92 - draft initial README.md with summarized paragraph of the one-pager
@@ -94,9 +94,9 @@ This is a comprehensive project plan outline for your data engineering pipeline.
94 94
95 95 ### Data Research Phase
96 96 - Identify potential data sources
97 - - Document data requirements (volume, velocity, variety)
98 - - Assess data quality needs
99 - - Determine necessary data formats and schemas
97 + - Document data requirements (volume, velocity, variety)
98 + - Assess data quality needs
99 + - Determine necessary data formats and schemas
100 100 - Create SQL database for data and document how it gets setup from scratch
101 101
102 102 ### Data Collection & Storage Setup
@@ -104,17 +104,19 @@ This is a comprehensive project plan outline for your data engineering pipeline.
104 104 - load from sources into SQL (pandas?)
105 105
106 106 ### Exploratory Data Analysis (EDA) Phase
107 - - Create initial Jupyter notebook
107 +
108 + - Create initial Jupyter notebook
108 109 - Perform basic statistical analysis
109 - - Check data distributions and patterns
110 - - Identify outliers and anomalies
111 - - Handle missing values
110 + - Check data distributions and patterns
111 + - Identify outliers and anomalies
112 + - Handle missing values
112 113 - Document initial findings
113 114 - Create data cleaning procedures
114 115
115 116 ### Advanced Analytics Phase
117 +
116 118 - Define key metrics and KPIs
117 - - Develop statistical models
119 + - Develop statistical models
118 120 - Implement feature engineering
119 121 - Create data transformation pipelines
120 122 - Validate analytical results
@@ -129,7 +131,8 @@ This is a comprehensive project plan outline for your data engineering pipeline.
129 131 - Document visualization components
130 132
131 133 ### Dashboard Creation
132 - - Design dashboard layout
134 +
135 + - Design dashboard layout sketch
133 136 - Implement dashboard components
134 137 - Create dashboard interactivity
135 138 - Add filtering capabilities
@@ -137,15 +140,16 @@ This is a comprehensive project plan outline for your data engineering pipeline.
137 140 - Document dashboard functionality
138 141
139 142 ### Flask Application Development
143 +
140 144 - Set up Flask project structure
141 145 - Create necessary routes and endpoints
142 146 - Implement authentication (if required)
143 147 - Connect dashboard components
144 - - Set up error handling
145 - - Implement logging
146 - - Create API documentation
147 148
148 149 ### (Extra Credit) Testing & Deployment
150 +
151 + _this phase is woth 1,000,000 extra credit points._
152 +
149 153 - Develop unit tests
150 154 - Perform integration testing
151 155 - Conduct user acceptance testing
@@ -154,7 +158,6 @@ This is a comprehensive project plan outline for your data engineering pipeline.
154 158 - Plan scaling strategy
155 159 - Document maintenance procedures
156 160
157 - _this phase is woth 1,000,000 extra credit points._
158 161
159 162
160 163

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1 file changed, 57 insertions, 59 deletions

PassionProj.md

@@ -13,7 +13,9 @@ In the Piro360 example, it is `Piro`
13 13
14 14 ## Method
15 15
16 - Perform each of these phases in order. [Java](#java) and [Data](#data)
16 + Perform each of these phases in order.
17 +
18 + ## 3-tier Web App
17 19
18 20 ## Create Repo for Project
19 21
@@ -21,8 +23,6 @@ Perform each of these phases in order. [Java](#java) and [Data](#data)
21 23 - draft initial README.md with summarized paragraph of the one-pager
22 24 - create a `src/` folder for all your source code
23 25
24 - ## <a name="java"></a>Java
25 -
26 26 ### REST Server (initial)
27 27 - Build a small, single entity (`Entity-1`) rest server.
28 28 - Load some test data into the db behind the REST server with a SQL file for Entity-1.
@@ -82,79 +82,77 @@ Perform each of these phases in order. [Java](#java) and [Data](#data)
82 82 - which brings up a Profile page
83 83 - how can you prove that your login page and its session security works?
84 84
85 - ## <a name="data"></a>Data
85 + ## Data Pipeline Project
86 86
87 87 This is a comprehensive project plan outline for your data engineering pipeline.
88 88
89 - ### Data Research & Requirements Phase
90 - - Define project objectives and success criteria
91 - - Identify potential data sources
92 - - Document data requirements (volume, velocity, variety)
93 - - Assess data quality needs
94 - - Determine necessary data formats and schemas
95 - - Create data dictionary template
89 + ## Create Repo for Project
90 +
91 + - add all your docs in a `doc/` folder
92 + - draft initial README.md with summarized paragraph of the one-pager
93 + - create a `src/` folder for all your source code
94 +
95 + ### Data Research Phase
96 + - Identify potential data sources
97 + - Document data requirements (volume, velocity, variety)
98 + - Assess data quality needs
99 + - Determine necessary data formats and schemas
100 + - Create SQL database for data and document how it gets setup from scratch
96 101
97 102 ### Data Collection & Storage Setup
98 - - Set up development environment
99 - - Establish data storage infrastructure
100 - - Create data ingestion pipelines
101 - - Implement data validation checks
102 - - Document data collection procedures
103 - - Set up version control for code and notebooks
103 + - Create data ingestion pipelines in python
104 + - load from sources into SQL (pandas?)
104 105
105 106 ### Exploratory Data Analysis (EDA) Phase
106 - - Create initial Jupyter notebook
107 - - Perform basic statistical analysis
108 - - Check data distributions and patterns
109 - - Identify outliers and anomalies
110 - - Handle missing values
111 - - Document initial findings
112 - - Create data cleaning procedures
107 + - Create initial Jupyter notebook
108 + - Perform basic statistical analysis
109 + - Check data distributions and patterns
110 + - Identify outliers and anomalies
111 + - Handle missing values
112 + - Document initial findings
113 + - Create data cleaning procedures
113 114
114 115 ### Advanced Analytics Phase
115 - - Define key metrics and KPIs
116 - - Develop statistical models
117 - - Implement feature engineering
118 - - Create data transformation pipelines
119 - - Validate analytical results
120 - - Document analytical methodologies
121 - - Optimize analysis procedures
116 + - Define key metrics and KPIs
117 + - Develop statistical models
118 + - Implement feature engineering
119 + - Create data transformation pipelines
120 + - Validate analytical results
122 121
123 122 ### Visualization Development
124 - - Select appropriate visualization libraries
125 - - Design initial visualization mockups
126 - - Create core visualizations
127 - - Implement interactive features
128 - - Ensure responsive design
129 - - Test visualization performance
130 - - Document visualization components
123 + - Select appropriate visualization libraries
124 + - Design initial visualization mockups
125 + - Create core visualizations
126 + - Implement interactive features?
127 + - Ensure responsive design (mobile and desktop?)
128 + - Test visualization performance
129 + - Document visualization components
131 130
132 131 ### Dashboard Creation
133 - - Design dashboard layout
134 - - Implement dashboard components
135 - - Create dashboard interactivity
136 - - Add filtering capabilities
137 - - Implement data refresh mechanisms
138 - - Ensure cross-browser compatibility
139 - - Document dashboard functionality
132 + - Design dashboard layout
133 + - Implement dashboard components
134 + - Create dashboard interactivity
135 + - Add filtering capabilities
136 + - Implement data refresh mechanisms
137 + - Document dashboard functionality
140 138
141 139 ### Flask Application Development
142 - - Set up Flask project structure
143 - - Create necessary routes and endpoints
144 - - Implement authentication (if required)
145 - - Connect dashboard components
146 - - Set up error handling
147 - - Implement logging
148 - - Create API documentation
140 + - Set up Flask project structure
141 + - Create necessary routes and endpoints
142 + - Implement authentication (if required)
143 + - Connect dashboard components
144 + - Set up error handling
145 + - Implement logging
146 + - Create API documentation
149 147
150 148 ### (Extra Credit) Testing & Deployment
151 - - Develop unit tests
152 - - Perform integration testing
153 - - Conduct user acceptance testing
154 - - Set up CI/CD pipeline
155 - - Create deployment documentation
156 - - Plan scaling strategy
157 - - Document maintenance procedures
149 + - Develop unit tests
150 + - Perform integration testing
151 + - Conduct user acceptance testing
152 + - Set up CI/CD pipeline
153 + - Create deployment documentation
154 + - Plan scaling strategy
155 + - Document maintenance procedures
158 156
159 157 _this phase is woth 1,000,000 extra credit points._
160 158
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