Introduction:
Big data is a hot topic in the Information Technology industry as it is a collection of data that describes the growth of the company, present in both structured and unstructured types. As the industry is dealing with large data, they are also concerned about the security of the data which is provided by big data security tools analytics.
Big Data Security Analytics is a collection of security data sets which are large and complex and it becomes difficult to process using the traditional database management tools or hands on database tools. These Analytics tools are primarily used for detecting threats in the large volumes of data by using multiple NoSql analytics that are provided by SIEMS or security management.
Problem identification:
SIEMS or any security management provides interfaces that create quiet a load on the systems and makes it difficult to sort and get the events that need attention. When interviewing small and mid-size companies I came to know that the databases provided by SIEMS cost a lot as the data that is used in NoSQL are unstructured and multi str...
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
Both passages concern the same topic, the Okefenokee Swamp. Yet, through the use of various techniques, the depictions of the swamp are entirely different. While Passage 1 relies on simplicity and admiration to publicize the swamp, Passage 2 uses explicitness and disgust to emphasize the discomfort the swamp brings to visitors.
After understanding the possible outcomes and usages of Big Data Mining and Analytics, the study of the process is necessary to identify the real possibilities behind this techniques and how this can improve a business performance. To do this; we should comprehend the basics about data mining and the process that leads from pure data to insights.
Big Data is a term used to refer to extremely large and complex data sets that have grown beyond the ability to manage and analyse them with traditional data processing tools. However, Big Data contains a lot of valuable information which if extracted successfully, it will help a lot for business, scientific research, to predict the upcoming epidemic and even determining traffic conditions in real time. Therefore, these data must be collected, organized, storage, search, sharing in a different way than usual. In this article, invite you and learn about Big Data, methods people use to exploit it and how it helps our life.
35 Meng Xiaofeng and Ci Xiang, 2013 : Big Data Management: Concepts,Techniques and Challenges pp 4-6
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.
Having greater speed and capacity is important; however how a business uses this new power determines the success of big data. Several advantages are factored into the use and application of big data. First of all, working with the information gathered can now be managed with less complicated steps than with previous programs. Since there is a large quantity of information cultivated, a requirement is to allow end users to find the appropriate information quickly. Big data applications can be run by non-information technology employees. The information is able to be manipulated efficiently as self-service analytic programs are being cultivated for all executives to have the ability to gain easy access. Charts, infographics, and dashboards are now accessible to more than the information technology specialists. The next application advantage is the evolution of data analysis methods and ...
Despite the numerous advantages offered by cloud computing, security is a big issue concerned with cloud computing. There are various security issues and concerns associated with cloud computing, among them being phishing, data loss and data privacy. There are different mitigation measures that cloud pioneers are currently using to ensure data stored in the cloud remain secure and confidential as intended. Encryption is one mitigation method used to ensure security in cloud computing. According to Krutz and Vines (2010), encryption involves coding of the data stored in the computing cloud such that hackers cannot gain access to the data. Data encryption seems to be the most effective method of ensuring security in computing (Krutz and Vines, 2010). However, it is of paramount importance to note that encrypted data is usually difficult to search or perform various calculations on it.
As the healthcare is increased day by day, it is very difficult to analysis the big and huge amount of the datasets. The healthcare data consists of the medicines data like drug molecules and structures and clinical trials, environment factors related to the health, lab reports, health insurance, and global disease survey etc. The healthcare big data analysis is the three step process: 1. Preprocessing 2. Cleaning 3.
When a company implements the use of data analytics, they are clearly looking to only improve the way the company functions on a daily basis by pin pointing possible solutions and verifying or dismissing certain ideas that may exist. The whole point of data analytics is that they give the company the opportunity to input raw data and data analytics makes sense of this raw data so that the company can use it to guide their choices. Data analytics makes decision making much easier and straighter forward than traditional accounting and business methods. It also provides the upper level employees of the company more exposure to the exact events that are occurring within the company. So, when it comes to the idea of having more information with
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.
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.