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15 Python Tips : How to Write Code Effectively

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 Here are some Python tips to keep in mind that will help you write clean, efficient, and bug-free code.     Python Tips for Effective Coding 1. Code Readability and PEP 8  Always aim for clean and readable code by following PEP 8 guidelines.  Use meaningful variable names, avoid excessively long lines (stick to 79 characters), and organize imports properly. 2. Use List Comprehensions List comprehensions are concise and often faster than regular for-loops. Example: squares = [x**2 for x in range(10)] instead of creating an empty list and appending each square value. 3. Take Advantage of Python’s Built-in Libraries  Libraries like itertools, collections, math, and datetime provide powerful functions and data structures that can simplify your code.   For example, collections.Counter can quickly count elements in a list, and itertools.chain can flatten nested lists. 4. Use enumerate Instead of Range     When you need both the index and the value in a loop, enumerate is a more Pyth
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Data analyst in FMCG sector the real opportunities

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[Demand for data analytics in FMCG]
[Demand for data analytics in FMCG]
Data analyst is a great demanding career in FMCG sector. The below are the key areas where data analytics can be applied in FMCG sector. There are many areas in FMCG sector one can get great insights. I have given some most useful thought that are being used in FMCG industry. The data engineer /Scientist must have great business knowledge to get true insights. However, as a software developer, this is just a working on analytics software as per guidelines prescribed by data scientists.

Consumers Business questions:

  • Where are your consumers?
  • Can you identify the characteristics that bond your consumers to the brands they buy? Can you segment your consumers using those characteristics and create a consumer purchase decision tree?
  • Can you access and translate the sentiment that your customers are saying about your company, your products and your customer service?
  • Can you share data with your retail and convenience store customers on a regular basis? 

R & D Business questions:

  • How do you ensure a new product meets our standards for safety, packaging or transportation?
  • Are you able to bring together all the data from your experimental tests and evaluate the results?
  • How can you quickly understand if a concept has already been patented and how will that impact our potential patents?

Marketing Business questions:

  • Can you analyse the effectiveness of each product?
  • How do you evaluate consumer research to truly understand the impact of a new product? Can you predict where your marketing spend will provide the best return on investment?
  • Can you predict future performance over the life-cycle of your brands?
  • How price-sensitive are your consumers? How price sensitive are your products?
  • How loyal are your consumers? What will make them switch to another brand and what is the threshold for switching?
  • What are the purchase attractors for your brands? How are these changing over time and how will they map against the changing demographics of your consumers?
  • Do you understand which marketing strategies your consumers respond to best?
  • Can you optimise your marketing spend across the marketing mix to drive profitable volume growth and revenue?

Sales Business Questions:

  • Can you optimise your trade plan in order to meet your business objectives?
  • How accurate are your demand forecasts and how easy are they to manage?
  • How much time do you spend forecasting?
  • Are you constantly trying to resolve internal forecasting conflicts? Are personal agendas contaminating what should be an ‘unbiased best guess’ at what is really going to happen?
  • Do you know what influences demand?
  • Can you gauge the impact of price changes and promotions and new product launches on demand?
  • Can you sense demand signals other than trend and seasonality (eg. price, sales promotions, marketing events, advertising, in-store merchandising), and then shape demand using ‘what-if’ analysis?
  • How do you decide what the promotions should look like?
  • Can you understand the overall ‘cost to serve’ for each customer?
  • If a customer starts a SKU rationalisation programme, would you know which products could be sacrificed without affecting profitablity?
  • Do you know how much space should be allocated to each product at the point of sale and where they should be positioned on the fixture?

Production Business questions:

  • What measures are there to ensure quality assurance throughout production?
  • Is your production process optimised to deliver against demand? Is it integrated with the forecasting process to avoid over- / under-production?
  • Can you identify production process costs throughout?
  • How do you manage and predict asset maintenance to ensure minimal production ‘downtime’?
  • How do you optimise human capital against production demands?
  • Can you accurately plan production to avoid over-/under-production?

Logistics Business questions:

  • How do you optimise distribution channels, case size, packing and truck loading?
  • Are shortcomings in your forecasting capabilities impacting warehouse space and workforce planning?
  • Can you identify excess costs within the process?
  • Can you optimise routes and transport methods to meet customer SLAs?
  • Are you adhering to your corporate sustainability programme?
  • How do you minimise the cost to serve a customer?

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