Variety. Variety is the different data types, representation and semantic interpretation. Dumbill (2012: 7) declares that “rarely does data present itself in a form perfectly ordered and ready for processing - it could be text from social networks, image data, a raw feed directly from a sensor source”. Value. Value is what matters to a person i.e. how valuable big data is to one. Benefits of big data Communication with customers Customers are not easy to study and predict; they look around a lot before they can make a purchase on a product. There are over 200 million blogs online and 34% of the post opinions about products and brands, and 90% of consumers trust the opinions (HP Enterprise Business, 2012). With big data you can profile the trends and even engage in real-time conversation. Re-develop products Big data helps you understand how people perceive your products; with data that is received with every purchase, you will be able to know how your products are received in the market. Perform risk analysis Continues scan and analysing of newspaper reports and social media feed...
Big Data is characterized by four key components, volume, velocity, variety, and value. Furthermore, Big Data can come from an array sources such as Facebook, Twitter, call
Companies like Under Armour and Nike are investing a lot of money in big data wearables. This line of products allows consumers to track their physical performance throughout their day or throughout their workouts. Under Armour provides their consumers with bigger company’s like
With multitudes of information shared on social media websites like Twitter, Facebook etc and discussions about company offerings on blogs, forums and posts; companies want to extract every bit of the information available to analyze consumer sentiments about their offerings. Companies from different domains are trying to use the customer sentiment information to gain a competitive edge in business. Below are some common industries that use sentiment analysis. Examples of companies within the domain are also mentioned to know the current users of Sentiment analysis.
...rces of Big Data . This huge amount of data possible for researchers to know the consumer behavior of customers , thereby refining the Internet of Things devices more suitable , we began serving daily lives of us more effectively . It can also be used for the production , thereby reducing human involvement . In the words of Daniel Kaufman predicted it " will do little more human " by Big Data .
Personal data is quickly becoming a commodity in today's high technology world. This information is used by banks, investment and brokerage companies, credit card merchants, government agencies (local, state and federal), and consumer product-based companies. Most people probably don't realize the amount of information that's shared between companies, or how often it's done. Many companies sell and share customer data to help sell products and find out what new products they should produce. Other uses include gathering information about inventory levels to help better determine what types of products are bought at which store, when and how often. This can be used for inventory and production, to make sure that the store (or stores for chains, like Safeway and Long's Drugs) can have the products available when they're needed.
Data can give you quite a bit of information about your customers. By examining it, you will be able to begin to see patterns and learn the habits of your customers. This could mean that you are able to provide the correct number of products at the perfect time instead of having a shortfall or being left with additional stock long after interest has fallen in the product.
If auditors can look at a complete population, they may not have a great defense if they missed a “smoking gun” since they looked at all the data (Alles and Glen). However, this data may not be valid which raises the importance of the auditor understanding where the data came from and how reliable it is. Not only this, it will be interesting to see how standards consider big data evidence. While it most likely will not be as reliable as confirmations, it would be a challenge to figure out how much the auditors could rely on it. Furthermore, higher education would most likely play a role in helping their graduates understand data and how to use technology to be not only more efficient but also ensure they are able to use sound professional judgement while using big data.
The key strategy implementation efforts at Amazon all surround the use of “big data”. Big data is the growth and availability of large volumes of structured/unstructured data. The use of big data has allowed decision making based upon data and analysis instead of past experience and intuition. Big data has directed organizational change in allowing Amazon to expand from an online book store to an internet giant. Revolutionary application of big data has allowed Amazon to create superior service quality while motivating employees by providing real time information to solve customer issues. Big data has strengthened Amazon’s competitive capabilities by pioneering the application of big data and charging a monthly fee to smaller businesses
You may ask what big data analytics is. Well according to SAS, the leading company in business analytics software and services describes big data analytics as “the process of examining big data to uncover hidden patterns, unknown correlations and other useful information that can be used to make better decisions.” As the goal of many companies which is to seek insights into the massive amount of structured, unstructured, and binary data at their disposal to improve business decisions and outcomes, it is evident why big data analytics is a big deal. “Big data differs from traditional data gathering due to that it captures, manages, and processes the data with low-latency. It also one or more of the listed characteristics: high volume, high velocity, or high variety. Big data comes from sensors, devices, video/audio, networks, log files, web, and social media which much of it is generated in real time and in a very large scale.”(IBM) In other words, companies moving towards big data analytics are able to see faster results but it continues to reach exceptional levels moving faster than the average person can maintain.
The data is already being generated as the use of blogs and online reviews increase. Sites like Amazon, the biggest online retailer, make reviews about products and sellers available and searchable for consumers. Aggregating 5 star ratings or binary measures, like recommend and not recommend, is not difficult, even with from thousands of records. However, free-form text comments are more difficult to summarize. Sorting and categorizing these opinions is called sentiment analysis. Companies already spend resources to research customer satisfaction and sentiment analysis is a great research tool for consumers and business.
Information privacy, or data privacy is the relationship between distribution of data, technology, the public expectation of privacy, and the legal and political issues surrounding them.
Big data originated with web search companies that encountered problems with querying large amounts of both structured and unstructured data. With regard to its background, “big data came into being when web search companies developed ways to perform distributed computing on large data sets on computer clusters” Floyer (2014: 1). Big data then spread to enterprises due to their adoption of developing, processing and dissemination of data.
Cloud computing is a type of computing that depends on sharing computing resources rather than having local servers or personal device to handle applications.
Data Protection is to do with you fundimental right to privacy, you may access and correct data that is about yourself. Anyone who keeps data about you has to comply with the data protection principles, there are 8 of these principles, and they are, 1. Fair obtaining, 2. Purpose specification, 3. Use and disclosure of information, 4. Security, 5. Accurate and up-to-date, 6. Adequate, relevant and not excessive, 7. Retention time, 8. Right of access. The following report is on an individuals rights and on an organisations responsibilities. It will guide you on how the rights and principles apply in different situations, like the use of CCTV or in the workplace.
Adopting big data can also help the banking industry by saving them from lots of embarrassment resulting from increase in the number of customer which in turn requires banks to improve on their performance. As stated earlier banks are entrusted with lots of information and this information must be safe will be required to be accessed ready and in a timely fashion. The use a normal small database will not be enough to perform this operation and if banks don’t embrace the use of big data they might start to experience failure in there system.