How to follow a Green Data approach

We have introduced the concept of Green Data several times in previous articles, but today we are going to tell in detail how this approach affects the entire life cycle of the data.

We live in an increasingly digital world, and this has big implications for the environment. Already, data centres consume 3% of all electricity produced around the globe.

And while that sounds like it’s a small piece of the puzzle, the world-wide production of aluminium, one of the most electricity-intensive industries out there, also only uses 3%.

For data centres, this percentage is only set to grow, as experts expect our total data storage and usage to more than double up to 181 zettabytes over the next four years.

Hence there is an increasing need of following Green(sustainable) approach.  

Below we see how a data life cycle should be done in the correct way with a Green Data approach. 

Green Data approach:

In “GREEN” Data, the term Green refers to sustainable process of Data collection, maintenance and processing.

The following steps help in adopting a Green Data approach:

In Data collection: Defining the purpose of data collection and the expected             outcomes to be drawn from the data and planning the schema of data collection before starting the project reduces the collection of redundant and obsolete data. Hence less utilisation of resources for data collection, less storage space, and less processing power.

In Data storage: Choice of site selection to reduce the cooling requirements, usage of low power servers, free air cooling, reusing waste heat, ultrasonic humidification, evaporative cooling, usage of renewable energy sources for the energy requirements of a data centre help in adopting a green data approach for data storage. Data centers that use renewable energy sources for maintenance are called green data centers.

Data Intelligence

We can define Data Intelligence as the analysis of various forms of data to extract their value. In the data pre-processing phase we create the basis for Artificial Intelligence, Machine Learning and Deep Learning to process data correctly.

Key steps to data sustainability:

Most organizations today collect far more data than they require for their business operations, simply because they can. The big problem is that a large percentage of the collected data is unused because it is redundant, obsolete, unstructured. By eliminating this data—or by not collecting it in the first place—businesses can cut down on storage requirements and costs while also supporting sustainability objectives by using less energy. But Green Data goes even further: it ensures that data is collected filtered, structured and correct.

To recap what has been said, here are some tips for starting a sustainable path with the data:

• Know your data footprint to follow the life cycle of data starting from data collection to the final stage
• Collect data in the right way
• Store only what you need
• Centralize data control for re-use

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