Experience the Power of Big data for Your Final Year Project Big Data 2017
The Importance of Big Data in Today’s Analytics Driven Business World
Gone are the days when businesses would make sense of their data through traditional analytics approaches. This is the age of complex data and only intelligent analytics can make sense of this data. Information in businesses is getting more and more complex and in order to make decisions from that information, companies must rely on the power of Big Data. This is the main reason you could execute a data and analytics intensive project for your Final Year Project Big Data 2017.
Big data technologies are designed to handle massive units of data. The three main aspects namely volume, velocity and variety of data are used for critical analytical decision making in businesses. Several examples of the use of Big data can be outlined when it comes to intelligent decision making. Social media is one of the most massive repositories of publicly available data that could be used for critical decision making.
Take for example the use of social media to track disease outbreaks though social media conversations. It is noted that when it comes to Big data decision making, the information is collected not just through social media, but a number of other information sources including web sources or mobile user information.
The Power of Big Data Analytics in Major Domains
Big Data is all set to change the way we see things in terms of technology and analytics. More and more professionals in the education, industry and other stakeholders are continually analyzing the influential power of Big data in prominent industries:
- In the banking industry, Big Data can be used to predict fraud and attacks that compromise security, assist in the audit process and provide valuable analytics for enterprise credit risk reporting
- The healthcare industry is one the most data intensive industry and inefficiencies in the smooth functioning of the healthcare systems is one the major reasons for the rising costs in healthcare. Big data can make several contributions in the healthcare industry from patient engagement to physician efficiencies and quality healthcare delivery
- In the media and entertainment industry, Big Data analytics can be used to collect and decipher insights on consumer behavior and choices and create the right leverage for social media.
- The Insurance industry is a rapidly growing industry and generates huge amounts of documentation in a number of sectors including healthcare, travel and property. The basic function of underwriting in the insurance industry is common to all types of insurance and this is where volumes of data in differing formats is generated for use with the claims processing. Big data has a number of different applications in the insurance industry including service enhancements and fraud detection and prevention.
- Education is another major industry, where the data comes from several different sources.Big Data applications can be deployed in the education field using a combination of data management techniques and analytics tools. One major area in the education field where Big data is used extensively is its use in Learning Management Systems
- In the natural resources industry, large volumes of data is generated which can be tapped using Big Data techniques, relying on the aspects of volume and velocity of Big Data to make sense the available data using analytics techniques such as predictive modeling for intelligent decision making.
- Manufacturing industries produce huge amounts of data that has to be consolidated and analyzed using Big Data techniques, to realize improvements in efficiency and experience increased profit margins and bottom line benefits.
- The Government faces several challenges in handling the ever increasing amounts of data because of difficulties in interoperability of data available in different formats and the integration of data available from different departments. The United States government departments such as the Food and drug Administration (FDA) for example, use the available data for efficient decision making
- Retail and wholesale outlets have numerous points where customer data related to buying preferences and customer experience can be collected and presented for Big Data analysis. Eventually, when analyzed in advanced Big Data tools, customer information can be converted into insights for retaining existing customers, converting new customers and promoting products and services
- The transportation industry uses big data for a number of comprehensive functions including controlling of traffic and management of congestion. Complex functions that involve whole cities require complex analytical techniques, which can only be addressed through the use of Big Data.
- Energy consumption and ways to conserve and improve energy use is one of the most important of the Big data domain. Analyzing energy use leads to insights into energy consumption through the use Big Data analytics.
Recommended Topics for Your Final Year Project Big Data 2017
In order to get a true picture of the data mining and the power of Big Data in Predictive Analytics, choosing to execute your Final Year Project Big Data 2017 based on one of the following would help you get a good understanding of the power of Big Data for future use:
Mining the education sector for data can be looked at from several different perspectives in the Big data realm in your Final Year Project Big Data 2017. Data mining the education sector can be challenging and might lead to information that leads to insights that can be converted to active decisions.
Predictive analytics in the subject of Business Intelligence has limitless applications. All businesses require analytics and Big Data analytics is an indispensable tool for dealing appropriately with any business problem. The different functions of any business including marketing, logistics, manufacturing or production require that Big Data analytics be implemented into their core decision making process so as to derive at decisions that make sense to business. Taking up your Final Year Project Big Data 2017 in the area of predictive analytics for business intelligence can help you gain answers to business problems accurately and with exactness and precision. Your knowledge gained as part of the academic project can be leveraged greatly and extended to solve real world business problems with ease.
Applying Big data on marketing analytics is a core function in any business. It not just helps understand existing markets clearly, but also helps capture new markets with ease. Big data is everywhere, available throughgenerated industrial data through IoT sensors for example or various other scientific and technical functions in any business. However, this huge amount of data must be used to generate effective insights and derive decisions through predictive analytics. Businesses need practical and innovative strategies in the Big data realm, to make sense of their businesses. By taking up a Final Year Project Big Data 2017 you might learn the right tools and get insights into the right techniques that will not just help make life more easier, but also make businesses more intelligent
Search engine analytics is another very interesting topic for your Final Year Project Big Data 2017. The amount of Internet data generated from searches is huge. Every second, million of terabytes of data is generated through search queries, keyword use and several other parameters. Tools that can be used to analyze search engine data can provide important data mining solutions. Your Search engine analytics is another very interesting topic for your Final Year Project Big Data 2017 which will help you gain insights into search engine monitoring tools, search parameters and search engine usage statistics.
Healthcare data is available through several different sources and the amount of healthcare data available is much more extensive when compared to data from any other source or related to any other domain. Healthcare data must be deciphered to arrive at various meaningful applications of healthcare data that would benefit patients immensely. One such area where Big Data modeling can be used is in the domain of preventive healthcare. For example, Big Data can be used to predict the disease state of a person even before the symptoms are apparent through the use of predictive analytics. Such approaches are very advanced in the healthcare domain and can only be realized through the use of Big Data techniques. Your Final Year Project Big Data 2017 could tap into healthcare domain data and unravel new techniques of preventing chronic diseases in a new light.
The world is undergoing drastic changes due to the impact of Big Data on various business functions. Information is continually distributed in the digital format and sensors are used to collect and disseminate information to stakeholders. Information generated in this form is used to visualize key trends. As information needs tend to scale by the day, so does the information generated, creating innumerable opportunities in the Big Data realm to decipher key associations between the data.
How Your Final Year Project Big Data 2017 Will Help You Enter into Mainstream Big Data Domain
Your Final Year Project Big Data 2017 could manipulate the key aspects of volume, variety and velocity of Big Data and find associations that will reduce costs and increase revenue and profits. Insights from Big data could make businesses more scalable and smarter.
Your Final Year Project Big Data 2017 could give you that much needed insight into the different roles Big Data engineers have to play for the successful execution of an information intensive project. Information that is available in the form of Big Data is generally handled by Big Data architects and Big Data engineers. The development, maintenance and testing of the Big Data solutions is carried by the Big Data engineers. Big Data Engineers can work with a number of front end and back end tools including MapReduce, Cassandra, Hive and NoSQL. Big Data engineers are generally software engineers who have acquired the right skillsets in object oriented programming, scalable systems, distributed programming and open source tools and techniques. Big Data engineers are capable of executing algorithms with a track record of high performance.
The most challenging aspect in the career of a Big Data engineer, which you will also encounter as part of your Final Year Project Big Data 2017 is the huge amounts of data that they have to handle everyday, in the range of not gigabytes, but petabytes or exabytes of data. Not only is the data overwhelming to the Big Data engineer, but the tools that he or she must e familiar also range from scripting languages, to databases and several data processing systems.
When it comes to the implementation aspects of complex data projects, the functions of collecting, managing, analyzing and visualizing information are key to Big Data engineering. Your Final Year Project Big Data 2017 will teach you these essential techniques when dealing with any Big Data problem.
Getting the right exposure through execution of your Final Year Project Big Data 2017 will enable you with the ability of executing complex programming logic with improved performance and unmatched user experiences. In this learning process during your Final Year Project Big Data 2017, you will be able to gain important skills like documentation, communication and project management with the help of hands on experience on business scenarios dealt with during your Final Year Project Big Data 2017.
Successful completion of your Final Year Project Big Data 2017 will enable you to get a peak into not just the role of the Big Data Engineer, but also a number of other data profiles including data manager, data scientist, data architect, data visualizer or data researcher.
Equipped with a solid grounding on not just Big Data techniques, but also career roles and working environment in the Big data realm, your Final Year Project Big Data 2017 will enable you to gain a wealth of experience during a few months through the expert guidance of industry experts available through a professional center involved in helping you complete your Final Year Project Big Data 2017. Getting to the final result of your Big Data project with the help of guides available at a professional coaching center, you will get the right expertise to step directly into a competitive Big data industry effortlessly.