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Big Data Applications

by Svitla Team

September 26, 2019
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What is Big Data?

No longer a buzzword and more of a wholly ingrained concept in our daily lives, Big Data is here to stay, grow, and evolve. Nowadays, Big Data is so important that it is now considered capital or an economic asset since a great deal of value is derived from the data that is generated on a daily basis from customer behavior, human interactions, sentiment, business activity, sensors, and much more.

Back in the early stages of Big Data, Gartner defined the concept, and his definition is still considered the go-to definition. In essence, it is “high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation.”

Big Data is data, but in a monumental volume, of magnificent variety, and produced at exceedingly high velocity. This is also referred to as the three Vs: 

  • Volume: High volumes of unstructured data.
  • Variety: Available types of data, namely structured, semistructured, and unstructured data.
  • Velocity: Fast rate at which data is received and acted upon.

In recent years, there are two more Vs that have emerged as important components of Big Data:

  • Veracity: The truthfulness of data and its reliability.
  • Value: Intrinsic value that can be discovered in data.

In reality, Big Data is so big and from so many different sources and complex data sets, that it has become virtually impossible to process via traditional data processing software. Thus, a variety of tools have emerged to process and analyze data, such as NoSQL databases, Hadoop, Cassandra, and many more. With the help of these Big Data analytics and processing tools, different types of data can be harnessed to collect, store, analyze, interpret, organize, etc. to glean insightful intelligence for better decision-making across all industries.

As stated by Gary King, Director of the Harvard Institute for Quantitative Social Science, “the march for quantification made possible by enormous new sources of data, will sweep through academia, business and government. There is no area that is going to be untouched.”

Now that we have explored the fundamentals of Big Data, for this article, we focus on the many and varied Big Data applications across different industries.

Applications of Big Data

As the world across every existing industry welcomes the age of Big Data, there are new and countless sources of streams of data and new sensors embedded in industrial equipment, automobiles, electrical devices, wearables, GPS trackers, and more.

Data is not only more available than ever before, but it is also more understandable with the utilization of computing intelligence through tools and technologies that facilitate its analysis. By gleaning knowledge and insights from the troves of available data, numerous applications of Big Data are coming to life, injecting new life into different areas of research, development, sales, business processes, and much more. Let’s explore the different industries that are experiencing radical and beneficial applications of Big Data.

Uses of Big Data in Marketing

Big Data is the best thing that has happened to the world of marketing since the introduction of the Internet.  With floods of data being generated by the second, marketers are on a race to design better, more effective marketing campaigns with the help of Big Data.  It is now possible to proactively target the core needs of customers through the use of rich and informative content. 

 Here are some noteworthy uses of big data integrated with a marketing strategy in marketing entities:

  • Boost customer engagement with powerful insights about customers - who they are, where they are, what they want, what they like, how they want to be contacted, and so on. Help create buyer personas by using data such as customer behavior, purchasing patterns, user background, and more.
  • Enhance customer retention and loyalty rates by identifying what influences loyalty and what keeps customers coming back repeatedly
  • Optimize marketing performance to help determine the most favorable marketing spend budget across different channels as well as continuously fine-tune marketing programs through testing, measurement, and analysis.

For example, cookie files. Companies collect cookies, which are small pieces of data sent from a website and stored on a user’s computer. These files help marketers manufacture tailor-made campaigns and design experiences that target specific audiences through unique, relevant content.

A clear example of Big Data in marketing comes to life with Coca-Cola. The company is well-known for using Big Data analytics to drive customer retention and strengthen its data strategy by building a digital-led loyalty program. In fact, Coca Cola was one of the first brands outside of the IT industry to speak about the benefits of Big Data. Back in 2012, Esat Sezer, the company’s former Chief Information Officer, said “social media, mobile applications, cloud computing, and e-commerce are combining to give companies like Coca-Cola an unprecedented toolset to change the way they approach IT. Behind all this, big data gives you the intelligence to cap it all off.”

In recent years, the sales of sugary drinks have declined and Coca Cola has tapped into its data wealth to produce and market healthier options, such as orange juice, under a number of proprietary brands such as Minute Maid and Simply Orange. The company combines weather data, satellite images, information on crop yields, pricing factors, and acidity and sweetness ratings, to ensure that orange crops grow in an optimum way, and maintain a consistent taste.

Another use of Big Data stems from social data mining. The company boasts over 107 million Facebook fans, who represent an important source of data. Coca Cola closely tracks how their products are represented across social media to calculate product mentions by the second. These insights help shape marketing campaigns by using algorithms to determine the best way to serve advertisements. According to the company, targeted ads based on these techniques have a four times greater chance of being clicked on than ads using other methods of targeted advertising.

Uses of Big Data in Banking and financial services

Banks are the perfect example of the type of entity that possesses and processes great sources of data. For banking institutions, Big Data offers many industry-specific solutions in terms of security, fraud detection, audit archives, enterprise credit risk reporting, data transformation, social analytics, compliance analytics, and much more.

American Express has jumped aboard the Big Data train by using the derived analytics to redefine their traditional banking strategies. By harnessing the power of internal data, the banking giant is migrating from legacy mainframes to Big Data processing environments to enhance speed and performance. With over 100 million credit cards in their database, American Express is capable of viewing all customer and merchant transactions in real-time to analyze trends and information about cardholder spending. With this analysis, it can create algorithms that tailor offers to attract and retain customers as well as nurture merchant relationships by tying the right customers with the right vendor.

Another example is showcased by the Securities Exchange Commission (SEC) which uses Big Data to monitor financial market activity through network analytics and natural language processing to catch illegal trading activity.

In the near future, banking and financial services are expected to further their use of the detailed information they have available about customers’ buying and investing habits. This data can bring new and exciting opportunities for customer service.

Uses of Big Data in Healthcare

The need for Big Data in healthcare rises as the diversity of possible applications becomes clear. From improved patient predictions, the use of Electronic Health Records, real-time alerting, enhanced patient engagement, informed strategic planning, predictive analytics, telemedicine, fraud reduction, and the potential cure of long-fought diseases, Big Data in healthcare brings many valuable benefits, with the ultimate goal of improving healthcare services and improving the overall life expectancy of all patients.

One of the biggest and most significant Big Data applications in healthcare is the use of Electronic Health Records (EHRs) by hospitals. EHRs include medical records such as laboratory test results, medical reports, lists of medicines, and more, and as they’re located in a centralized location, it is easy to maintain and have access to such data.

A real-life example is showcased by Alameda county hospitals in California, with a U.S. program called PreManage ED. With this program, patient records t such as tests at other hospitals or patient advice issued from other facilities are shared with emergency departments. This helps ensure o that the patient receives timely attention, provides details of previous tests and avoids unnecessary formalities.

Another example is shown by the Israeli company named MedAware which is using Big Data to eliminate medication errors caused by human factors. The patent-pending technology uses big data analytics and machine learning algorithms to analyze large-scale data in electronic medical records to automatically learn how physicians treat patients in real-life scenarios. Ideally, the technology used by MedAware flags potential errors with high specificity when prescriptions deviate from standard treatment patterns. According to MedAware, this solution could help save more than $13 billion in direct annual costs associated with prescription errors.

Uses of Big Data in Education

Big Data helps clarify educational needs at the local and federal level to ensure the best methods and tools are being deployed. The education industry generates a flood of data related to students, faculty, courses, results, records, and more. This data is full of potential insights that can help improve operational efficiency and the working conditions of educational institutes.

The key benefits of Big Data applications in education include customized and dynamic learning programs, update of course material, advanced grading systems, career prediction, and much more.

One example is the University of Tasmania which has deployed a Learning Management System that tracks when students log in, how much time is spent on different pages of the system, and the overall progress of students over time.

Another example is the University of Alabama which implemented a big data strategy where administrators can use analytics and data visualizations to derive trends and patterns hidden in the data of over 38,000 students, thus revolutionizing the university’s operational, recruiting, and retention efforts.

Uses of Big Data in Government

One of the key benefits of big data is that it can bring value to everyone. Governments, which are sometimes thought of as slow adopters of new technologies, have embraced Big Data as a driver for solutions and varied applications, including energy exploration, financial market analysis, fraud detection, health research, environmental protection, public transportation, traffic congestion, crime prevention, and much more.

With Big Data platforms, governments can access massive amounts of data. For example, the Food and Drug Administration (FDA) uses big data to detect and study patterns of illnesses and diseases that are food-related. Another application of Big Data that the FDA leverages is the faster rate of innovations in clinical trials and medical product development. According to FDA Commissioner Scott Gottlieb, “our longstanding goal for medical care is to ensure that the right drug or device is delivered to the right patient at the right time.”

For government organizations, another key application of Big Data is represented by possessing the means to analyze patterns and influence election results.

Uses of Big Data in Media and Entertainment

Already, Big Data is transforming the way studies about social networks are conducted, as research involves mining huge digital data assets of collective online behavior. By deep-analyzing a given social network platform, researchers can identify patterns of influence and peaks in communication on a particular subject.  An example would be by following a hashtag on Twitter.

In a generation where instant gratification is highly coveted, the media and entertainment industry is searching for new ways to analyze customer data and behavioral data to create customer profiles and generate content for different target audiences, recommend content on-demand, and measure content performance.

One of the most famous applications of Big Data is showcased by the huge streaming service Netflix as it has comprehensive recommendation systems that are data-fed by over 100 million users, thus offering attractive and tailor-made suggestions about TV shows and movies that could appeal to specific users. Big Data helped  Netflix build powerful algorithms that ultimately helped save over $1 billion in value from customer retention programs.

Famous applications of Big Data also include the case of Spotify,  which is wholly data-driven. On a daily basis, nearly 4 terabytes of data that are used in Hadoop big data analytics to provide music recommendations.

Uses of Big Data in Transportation

Big Data is used in the transportation industry to oversee and ensure better roads, secure roadways, enhance routes, safeguard traffic levels, manage congestion, and develop new roads.

A popular example of a big data application in transportation is Uber. Uber is deeply rooted in data and generates monumental amounts of it in reference to drivers, vehicles, surge pricing, ratings, estimate fares, locations, distance, maps, and much more. 

With a massive driver database, Uber uses an algorithm that gets to work as soon as a user requests a car. This algorithm matches the nearest driver to the client, and in the background, stores data for every trip taken. This data is used by Uber to predict supply and demand, as well as set fares. Another use of big data involves the examination of traffic bottlenecks and other transportation issues to find ways to keep traffic running smoothly. 

Importance of using Big Data software

For 2018, the expected annual revenue from the global big data market was supposed to reach $42 billion dollars, with predictions suggesting that this figure will only continue to grow exponentially in the following years. The major providers of big data services include tech giants such as IBM, Dell, Oracle, SAP, AWS, Cloudera, Microsoft, Splunk, HPE, and Accenture, to name a few. For more details, the computer magazine Datamation posted a list of the Top 20 Big Data Software applications.

Big Data software is big news. The possibilities of managing and utilizing data are immense. Below are a few important ways that Big Data software can transform an organization.

Distributed computing

Model in which software system components are shared between multiple computers. Distributed computing studies distributed systems whose components are on different networked computers, which communicate and coordinate actions and messages.

Data visualization

Graphical representation of information and data that helps organizations use an accessible method to see and understand trends and patterns in data by showcasing them via charts, graphs, and maps.

Business Intelligence

Technology-driven process of analyzing data and presenting actionable information to make informed business decisions. Business intelligence can be thought of as a set of technologies and strategies that provide historical, current and predictive views of business operations.

Data lakes

Central storage repositories that hold big data from many sources in raw format. With data lakes, data is associated with identifiers and metadata tags for quick retrieval and analysis. Thus, data scientists can access, prepare, and analyze data faster and with more accuracy to yield better results for organizations.

The next stages of Big Data applications development

Big Data is changing the way businesses market to their customers and how they execute their operations. With more information pouring in, the decision-making process is greatly enhanced, resulting in noticeable profits as this BARC research report shows.  There’s an increase of eight percent in profits and a reduction of approximately ten percent in overall costs from surveyed businesses.

The future holds the promise of a world where businesses, with the alliance of Big Data and Artificial Intelligence, not only capture data effectively but turn it into actionable value and actually use it intelligently and autonomously. In essence, future systems will take data and act upon it as the agents of organizations, without any human intervention.

To further examine the next stages of Big Data, let’s take a look at some of the most prominent trends:

In-memory technology

In an attempt to speed up big data processing, companies are looking into in-memory technology where data is stored in RAM, which is significantly faster than other storage solutions.

Machine learning

Already, machine learning and big data have joined forces to develop comprehensive systems to process and analyze data, but as capabilities progress, the future only gets brighter for these two allies. The goal is to create systems that understand, learn, predict, adapt, and potentially operate autonomously.

Predictive analytics

A close relative of machine learning, predictive analytics uses big data to predict the future. This represents a huge advantage for businesses that want a competitive edge.

Intelligent apps

By incorporating big data, intelligent apps can personalize and enhance customer service through recommendation engines, such as the ones we’re seeing across many e-commerce and entertainment apps.

Internet of Things

With more devices being used daily and thus more data generated,  big data can help organizations experience even faster data growth to handle and make sense of it.

Edge computing

With edge computing, big data analysis happens side by side with Internet of Things devices and sensors, instead of it occurring in a data center or in the cloud.

Time and again, big data continues to demonstrate that it unlocks potential and it holds an even greater promise for the future. With this in mind, at Svitla Systems we recognize and value the capital that is big data and the many applications that can be seen across all industries.

Be successful with Svitla Systems

If you want your company or project to successfully join the Big Data movement, partner with Svitla Systems.  We have teams of highly-developed, highly-skilled experts who are ready to assist you with end-to-end solutions that address your big data processing needs.

In the hope that this article was helpful and informative, be sure to reach out to our sales team or fill out the request form below for more information and details. We are here to help you in every way we can.

Our work

Take a peek at some key case studies that showcase our work in big data projects Intermune, Ancestry and Goodhire.

by Svitla Team
September 26, 2019

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