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How Big Data Could End Up Helping Lower Income Families

Big Data Use Cases

7Dec

Big data exploded on the scene as a tool to help companies gain insights on what their audiences want the most. This greater information allows them to tailor their products, adjust their budgets, and cater to new trends in order to make more revenue. With profits in mind, it’s easy to think big data can do nothing for those with lesser income or no income at all, who aren’t running a company and do not have the means to do so.

However, as more industries are making use of the tool via technological advances like hyper converged infrastructure, big data may in fact be able to help lower income families – not only in a monetary way, but in improving their daily lives.

1. Credit and Recognition

Building a quality credit history is a difficult task for anyone, but for the less fortunate, it can be next to impossible. A troubled time can lead to foreclosure or repossessions, deeply harming your credit score. A lack of opportunity and funds, leading to a complete lack of credit history, can ensure that banks look the other way when you ask for a loan. To make things even worse, with few transaction receipts to your name, much of the market will ignore you for higher paying customers.

Yet big data is here to change all of that; even if you do not have the funds to buy a house or car, you likely have access to the internet in one form or another. You leave a footprint of data by simply browsing around and clicking on ads, and this is the sort of information will be used to determine an audience’s tastes, new trends, and more, creating a more accurate assessment of what people want and do despite their income. This means even those without financial clout can have their voices heard, helping to draw attention to the lower income needs and boost the economy. In addition to this, the history you build on the web may soon become a substitute for traditional credit, as banks can view your habits, likelihood to repay, and so on.

2. More Focused Aid

Poverty is a widespread problem in the world, and natural disasters can lead these impoverished areas to ruin. Big data is all about using a wealth of information to offer more focused and accurate results, and this applies to more than simply marketing. By gathering information from past occurrences, big data could predict disasters such as droughts, earthquakes and more, allowing the government or helpful organizations to offer aid in advance to ensure such a disaster does not harm the population.

In addition to this, the internet footprint of the people will allow organizations to discern which areas are in most need and what methods would be the best for helping them. This gives them access to real-time, boots-on-the-ground intelligence on the condition of certain areas, the level of aid they need, and the techniques required for helping them.

3. More Efficient Non-profit Organizations

Organizations set on offering aid can only manage that task if they’re running efficiently themselves. This can be especially difficult with non-profits, which are highly accountable for their funds, may not have the appropriate numbers to fund each of their branches, and must evolve independently with changes over time. This leads to a struggle in allocating funds; which branches should be cut, which divisions should have more funding, how decisons are made efficiently, etc. The key to big data is taking all of this information, throwing it into a great pool of resources, and then both isolating and focusing on the crucial elements. By doing so, organizations can gather more accurate insights on how to manage their operation and ensure it continues to be successful.

Poverty means less access to opportunities, and even the largest organizations can become lost in their own branches and divisions, unable to offer those sought-after opportunities and help to others. In the same way big data delivers focus, BI analytics, and solid information to make large companies rich, it can also apply this same advantage to impoverished nations, people in need of loans, and organizations looking to broaden their reach to help others in need.

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