Big data is a term that refers to data sets that are so complex or so large such that ordinary data processing applications can’t process them. The data in these sets could be structured or unstructured.

Top 4 Uses of Big Data

Big data has numerous uses. Here are four of them:

  1. Prediction of Heart Disease

According to Ben Davis of Econsultancy, IBM is using big data to predict the possible occurrence of heart diseases. By analyzing the data from electronic health records, symptoms of heart disease can be noticed at a much earlier stage. When perfected, this technology could be used to significantly reduce the rate of cardiac failure in the future.

  1. Predicting Future Disease Outbreaks

By observing data from local climates and temperature patterns, IBM has been able to find correlations with how Malaria spreads. It makes it possible for them to predict future outbreaks of such diseases.

Predicting Future Disease Outbreaks

  1. Weather Forecast

The App, WeatherSignal, uses the sensors in Android devices to forecast the weather. Some devices contain a barometer, hygrometer and light meter. All the data collected from these devices is sent to one location from where it is analyzed.

  1. Business Analysis

The analysis of big data can reveal flaws in a business and save it before it collapses. For instance, the analysis of such data can pin point the potential loss of customers from a certain company and why those customers will be leaving the company. The said company would then be able to adjust its services in time for it to retain that very important customer.

Challenges Facing Big Data Analytical Companies

Here are the challenges faced by the companies that analyze big data:

  1. Identifying the Data

There is so much data everywhere. Companies that deal with big data have a big problem when it comes to identifying which data is important to them and which is not. In addition to this, these companies also face a challenge of knowing what to do with the data that they collect.

  1. Identifying Capable Talents

Dealing with big data often requires people with the capability of working with new and fast evolving technology. It also needs people who are able to interpret their findings and transform them into meaningful business insights. Currently, finding such people is one of the biggest challenges that the companies dealing with big data analysis are facing.

  1. Access to The Data

According to Eric Spiegel of the Wall Street Journal, most of the data points available to such companies are not connected. In addition to that, most companies lack the right platform to collect and manage the data.

Identifying Capable Talents

  1. Fast Technological Evolution

The technology involved in the analysis of big data is quickly evolving to be able to better cope with the requirements of the field. Therefore, for analysis companies to be able to keep up, they have to couple up with a strong technological partner who can assist them create the right plan and equip them with the tools that can quickly adapt to the changes.

  1. Security

Big data exists in a realm where security is a major concern. The security threats that face the data and the companies that deal with it prevent them from utilizing it to the maximum.

  1. Getting maximum value for their data

The data that big data analytical companies deal with is measured in zettabytes. A zettabyte is the equivalent of sextillion bytes. The customers of these companies often demand accurate and comparative results. Under the current circumstances, meeting the demands of the clients requires facing a multitude of privacy pitfalls and security issues that must all be avoided. Doing all this is tedious and in the end, the value of the data is really low.

  1. Displaying The Results

One of the methods for displaying results is using graphs. However, if we put into consideration how much data is involved, plotting a graph to represent it seems like an impossible task. In fact, according to SaS, plotting graphs for such large amounts of data is a huge challenge for those working with it.

Getting maximum value for their data

  1. Storage

The companies that deal with the analysis of big data need a lot of storage to store the unprocessed and processed data. The data could be in form of:

  • Audio files
  • Images
  • Messaging streams
  • Voicemails
  • Geolocations just to name a few

Even with cloud storages, some companies still face storage issues.

There are is so much importance of big data analysis results. Once the challenges listed above have been overcome, the results can be used to improve various aspects of life. However, overcoming the challenges is not an easy task.