Big Data- What It Means and Its Real-Life Applications
Big data is a branch of data science that deals with large data sets. Traditional data processing can’t handle chunks of info of such size therefore the quantity of digital data today is enormous. A single mobile device generates terabytes of information. The same goes for web pages. There’re billions of both as of today. In 2001, there was less than a single exabyte of digital data. However, as early as 2007, the number was 280 exabytes. Weekly, petabytes of new data have been coming into the equation. The rise of the internet has increased the amount tenfold hence, scientists work hard to come up with ideas to process the tons of info. It’s the place of BD to fill in the blanks.
Big data analysis is valuable as it defines the way the modern world operates. It also helps us process chunks of information that regular software can’t tackle. It does it faster and with better accuracy. In this way, scientists can come up with better results in their research. Note, big data is an umbrella term that covers several fields:
- Predictive analytics;
- User behavior analytics;
- Advanced analytics techniques that derive value from statistics;
You can find references to BD in all these fields. However, other terms you’ll come across include Data:
They all have their meaning in the context of big data. All of them represent some of the biggest challenges in the field, as well.
Its challenges demonstrate the weak points of the method. They also warn against the potential shortcomings of the results. However, it’s not all bad. The ability to overcome any of the major cons will lead to a high-tech leap forward.
Imagine the amount of data the IT Age produces. This alone calls for better processing methods. That’s where BD comes into the picture. Corporations like Microsoft and IBM rely on the technique to function. More and more governments also do the same. The real-life applications of big data are in the modern economy. Healthcare, technology, and marketing also benefit. To learn how to apply it to your sphere of work, ask our experts at Dexivo. They will be happy to help you optimize your business as well as its efficiency.
Big Data in Government
Innovations, cost reductions, and improved efficiency. BD offers all of these to governments. It also stimulates agencies to cooperate. The more they work hand-in-hand toward a common goal, the better. Critics tend to stress the problems of such cooperation. One can’t ignore the positive outcomes of it, though. They become evident in the long run.
Big Data and Global Development
Global development is one of the biggest challenges of modern culture. The tools of BD offer unique perspectives on the issue. It can also provide a solution. They provide possible outcomes from efforts in improving:
- Crime reduction;
- Economic yield;
- Resource management;
- Natural disaster management;
Traditional predictive analytics managed to do the same. But there was a difference – the scale. The old algorithms performed predictions for limited geographic areas. BD analytics operates throughout the world. The results are reliable and come with a manageable schedule.
Specialists point out another positive side of BD in that regard. It gives the world a chance to hear the voice of people who suffer oppression.
The challenges here come as no surprise. The method works well in developed countries. In lesser developed countries, it is not so simple. The below hampers the analysis of relevant data:
- Lack of On-premises hardware;
- Fewer warehouses;
- Slow internet connection;
- Not enough specialists;
- Political issues;
How can we solve these issues? Most experts suggest:
- Economic development;
- Working for political freedoms;
- Improvements in internet connections;
Though these things won’t be enough, they’re going to be a good start.
Applications in Healthcare
Prescriptive analytics is what BD contributes to healthcare as well as personalized medical care. There are other cons for the medical field, like:
- Reduction of care variables;
- Reduction of waste;
- Predictive analytics;
- Clinical risk intervention;
- Automated reporting of patient data;
- Fragmented point solutions;
It’s important to remember that BD hasn’t come to the end of the road. Some solutions have real-life applications today; others are just goals. Data scientists still have a lot of work to do to reach them. New technologies also increase the amount of data healthcare generates. Take wearable technologies. They track patient stats in real-time. The information goes into the data lake therefore, data management experts use it right away. Doctors rely more on computer-aided diagnostics today therefore, it wouldn’t have been the case without BD. For instance, Let’s look at epilepsy monitoring. It’s typical for the process to create ten gigabytes of data. That’s every day for a single patient. Add up the information for patients in the United States for a year. You easily reach petabytes. These volumes of information run through BD analytics. Then, they provide new insights into medical conditions.
BD holds promise for the field of bio-metrical research. Data-driven analytics do better and offer structure:
- Researchers use big-data analysis to form a theory;
- They predict the outcome from the information the data sets contain;
- They go on to testing the theory in the traditional environment;
What’s the benefit of such an approach? It saves tons of time, resources, and mistakes. No one can argue the benefits. However, the next leap forward for healthcare will come from the BD platforms for sure.
Big Data and Education
Various studies have shown there’s a shortage of data scientists on the market therefore schools and other scholarly institutions have taken measures to fill that gap. You can get a degree that qualifies you to work with BD. Berkeley is one place to provide such. Others include the Data Incubator and General Assembly. These businesses also create private boot camps to meet the demands of their institutions. Some industries operate with large amounts of different types of data. They can’t rely on a unified BD analytics method. Such a thing doesn’t exist. Marketing is one of the fields where that’s evident. Digital marketing specialists work in several sub-categories:
- Product Development
Schools address the issue in several ways. They introduce aspiring marketers to a range of analytic tools because it is the only way to give them the skills to produce optimal results. The lack of specialists is one of the challenges the sector faces. Therefore, researchers suggest 1.5 million more experts have to enter the field. The industry needs people who know how to perform:
- Data collection;
- Data mining;
- Data Storage;
- Integration of ideas;
However, it comes as no surprise that United States colleges are opening new programs. Experts also think the demand for such programs will increase in the next ten years.
Read More on : Data Protection Policy
Media Use of Big Data
Digital media uses BD a lot. They also apply a holistic approach to information and blurs the boundaries between outlets. Media workers can reach a wider audience in such a manner. The analysis of BD helps grasp the mindset of the target public. As a result, the content speaks to the consumer on a personal level.
Data journalism allows for unique insights into the data lake. Journalists also use BD to produce infographics, as well. They can help explain complicated issues in a more accessible manner. The hope is that BD will make journalism less biased. The data tells the truth, right? Careful analysis of the data sets makes it easy to see.
The Internet of Things (IoT) and the Data Lake
Internet of Things describes physical objects that use sensors and software. They collect and share data with other devices over the internet therefore it can’t exist without BD. The IoT info creates a map of the connections between devices. Media corporations also use it to target audiences better. Governments and marketing companies do the same. BD has a great influence on business decisions in the modern age.
The Four Vs of Big Data
Researchers divide big data into four parts. They are volume, variety, velocity, and veracity. Each one represents the vital qualities of the info from the data sets.
1. Volume – the sheer volume of data is what makes it “big” in the first place. Adding new data storage units isn’t enough to keep up. Some estimates show the volume increases by 50% every year. There are predictions for an increase in that rate as well.
2. Variety – it represents a curious quality of BD. It involves traditional structured data and unstructured data. Structured data includes dates, bank account numbers, and such. Unstructured data sets include social media feeds, web pages, and logs. Unstructured data lays the foundations of BD. Not only this, but it offers a glimpse into human nature. Structured data can’t provide such insights.
3. Veracity – it shows how reliable the data is. It’s impossible to gather data you can trust one hundred percent. The question is, how much of the data set is reliable?
4. Value – the first three Vs have no real meaning if there isn’t value to them. The value aspect represents the value of the analysis. The aim is to optimize the customer experience. It’s not all about money, though. It can manifest itself in the chance of finding a new cure for a disease. Or medical treatment for a particular patient.
Insight into the four is vital for performing BD analysis. Integrate them into your data analytics. It’ll help you make better business decisions as well as benefit the well-being of your consumers as well. We at Dexivo will gladly help you out with this.
Challenges and Pros and Cons of the Method
Like everything in life, big data has its positive and negative sides. The pros of BD are that it:
- Improves decision-making;
- Increases capacity;
- Brings down costs;
- Betters customer service and customer experience;
- Optimizes revenues;
- Helps fraud detection;
- Improves agility;
- Widens the space for innovation;
- Speeds up the process of putting a product on the market;
No one can deny that these are all good things. We at Dexivo can help your business reap all benefits of big data. We’ll also help you avoid suffering from its negative sides as well. However, one shouldn’t forget that there are two sides to every coin. The cons of BD that critics point out include:
- Lack of enough qualified specialists;
- The quality of the data is debatable;
- Big data analytics aren’t a major part of corporate culture;
- Government regulations and compliance;
- The rapid pace of high-tech advances and changes;
- There aren’t enough data warehouses and efficient hardware for them;
- Problems with the integration of legacy systems;
These represent serious challenges. It’s the reason full BD technology integration isn’t a reality. Most of the problems also show the most evident drawbacks of BD. Artificial intelligence will help mitigate a part of the risks. Experts have hopes for machine learning as well. As of today, though, the technology is in its infancy.
Open Source Technology at Its Best
Apache Hadoop is a set of open-source tools. They create a network of computers. Once the devices are in connection, they can solve certain problems together. NoSQL databases find an application here. Therefore, traditional relational databases don’t work with unstructured data – it’s their nature. The power to compute large data sets from the data lake is much greater so you can say Hadoop makes cloud technology a reality. The principles of Hadoop make services like Cloudera work. Things that are achievable thanks to it involve data:
- Visualization tools
Open source technology is helpful in their development. It also stimulates cooperation between specialists worldwide.
If you wonder how you could integrate big data in your business, stop. Give Dexivo a call, and we will figure it out for you. Our experts will also show you how to improve decision-making. Then you can enjoy higher profits thanks to BD analysis. The method will also make your customers happier. BD has the potential of changing the future of humanity for the better. Be a part of the change today.
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