For the rural farmer, does big data raise more questions than answers?
The great challenge remains as to how to effectively get the actual data from data scientists to the farmers
Photo by Charles Knowles
“The price of light is less than the cost of darkness.”
These words by Arthur Nielson speak enough truth to the importance of data today.
Data is produced at such high frequency and volume that it is undoubtedly very important in all spheres of business.
We cannot emphasize enough the value of big data especially in the agriculture sector where, in the face of climate change, it requires well-informed decision making.
Big data all over the world is being used to provide predictive insights into farming, redesign some business practices and even drive real-time operations in farm management.
Venture capital has flooded digital agriculture in a bid to revolutionize the food chain. However, the greater challenge remains how we can ensure that this is done effectively from the actual data to data scientists to farmers.
This being especially important for developing nations where challenges of network coverage and digital literacy are still relevant.
For the literate farmer, it’s easy to use online web applications, dashboards and charts to understand what will go on your farm, when and at what time.
However, for many who practice agriculture especially in rural areas, data represented in this form may be a bit too much to understand that is assuming they have access to network coverage, digital platforms or devices that would facilitate access to this data.
So how will a farmer in the rural area make use of big data?
To realize data’s potential, we need to make it accessible and the answer could simply be found in those tiny devices we walk around with, in our pockets every day, the mobile phone.
The beauty of the mobile phone, whether feature phone or smartphone, is that it allows for timely communication in both text and voice messages.
Now with the kind of technology we have today, data that has been published on a dashboard can be broken down into simple information, converted to a variety of formats and send out as a text or voice message to any type of phone.
Hence allowing a majority of the population that have a mobile phone to gain from this information and not just farmers in the position of advantage.
Big data is amazing. However, it is easy for many to fall into the trap and hype of it and embark on many initiatives and projects without clearly understanding the value it intends to bring.
The first thing to overcome is in defining what big data means.
It has often been described in the 5 V’s. Velocity to mean the speed in which it comes, Volume to mean the vast amount of data, Variety referring to the types of data, Veracity referring to how messy the data is and its accuracy, and most importantly Value which speaks to the ability to turn the data into something of value.
Considering an understanding of the type of data involved, how do we ensure that it is available in a presentable, simple form and reaches the right user?
To unlock data’s full potential in agriculture, the right data should be accessible and communicated in a form that can be understood and is specific to the needs of the farmer.
Important questions need to be answered such as: What data is relevant? What is the end goal and how will the data achieve these goals?
For these questions to be addressed, the end users, farmers, need to be part of shaping the process.
They would assist in informing what data is necessary, how it will make sense to a farmer and in what language and at what time this information is of most value to them.
We can also fully realize the value of big data by employing a digital data platform that works for agriculture.
Suitable architecture designs that compliment tools like Hadoop/NoSQL databases may be needed to break down data and ensure the right information gets to the right user but it is important to know that data platforms are not a ‘one size fits all’.
Hence to complement the organization’s work, it is important to assess and strategize.
I may not be an expert in this field but based on my profession, Geospatial Information Systems (GIS), I do know the vast amounts of data a geographical information system can produce. I also know that while tools that support big data are key, they only work efficiently when the whole design fits the organization’s needs.
To ensure right data gets to the right user, the right tailored data platform is key.
GIS for big data analysis has been one such platform as a tool that helps in the geographic assortment of big data.
With GIS one can attribute every crop information to a specific location hence ensuring the data of a particular region is reached by farmers of the same region. For example, maize that is grown in Kenya’s Machakos County might not experience similar climatic conditions or face the same disease risks as that grown in Uasin Gishu County. As such, we deduce that it is crucial to attribute all data to a location.
There is much work needed to implement the correct infrastructure from the start, and there is no one single way to approach these questions.
Data and especially big data is reshaping how we have always perceived agriculture.
Often we wonder why sectors such as banking are thriving but agriculture continues to be underperforming.
The main difference is that other thriving sectors, unlike agriculture, have a formal baseline and like most formal businesses, their efficiency increases with employing technology and data.
Likewise to ensure agriculture thrives we need to take it with the same level of formality and employ the digital transformations of today.
Ultimately, the goal is to turn data into information and information into insight for farmers and not to allow the sector to be left behind.
Like Malcolm X put it: “The future belongs to those who prepare for it.”
Sophia Njeri Murage
Geographic Information System (GIS) Consultant with a keen interest in digital agriculture and the potential benefit spatial and big data would have in the sector
Blog Competition Entry
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