Web Analytics {Comments Off on Web Analytics}

By Gavini K.

Web analytics plays a huge role in many different ways through today’s technology. It helps many industries like health, finance and business. Web analytics is the gathering of data through the web, and analyzing them and making predictions. “Using machine-learning algorithms, and artificial neural networks, Web analytics software finds useful hidden information and patterns in the data and uses them to form new rules and predict the future behavior of customers, turning that mountain of data “Big Data” into valuable knowledge and untapped business opportunities and to enhance customer experience management (CEM) and customer relationship management (CRM). Customer relationship management system is an information system that provides an integrated approach to all aspects of interaction a company has with its customers (Brown, 2012).” Web analytics has become a huge impact on the world, most importantly in business. It has given us so much information to which it has shown businesses a path to making the companies succeed and make the customer relationship strong. There are three examples that prove just this.


Future Business Decisions with Prescriptive Analytics {Comments Off on Future Business Decisions with Prescriptive Analytics}

By Jerome F.

We live in an age where technology has far surpassed our expectations and has exponentially grown over the course of the past several decades. With these rapid technological advancements, it is has become more increasingly complex for organizations to examine data that will benefit their own business. Organizations remedy this issue by examining these raw data through the utilization of data analytics, a concept that is used by implementing three key ideas to create better efficient business decisions. Prescriptive analysis, the third and final phase in this process, wraps everything up and formulates recommended actions for organizations to move towards for desirable outcomes.


Business Intelligence & Descriptive Analytics {Comments Off on Business Intelligence & Descriptive Analytics}

By Carlos A.

Business intelligence is the process in which a business collects data and information from its operations and environment to help make strategic decisions. Business intelligence includes many difference types of applications, systems, and tools that are used to collect data and give the data meaning. An important area of Business intelligence is descriptive analytics in which a company performs an analysis of data to gain insight into its business’s past performance (Bertolucci, 1). Descriptive analytics are a form of analytics that help describe what has happened in the past and make it easier to notice changes and trends in a business.


Problem Solving Using Descriptive Analytics {Comments Off on Problem Solving Using Descriptive Analytics}

By Jeffrey A.

Descriptive analytics has to do very heavily with business intelligence. It is often considered the first step in gathering business intelligence because of its relation to big data, which is large collections of information gathered by corporations or other entities. This is often done for the purpose of developing reports or creating forecasts, but it is not possible without accurate and proper data collection methods. Other forms of analytics include predictive and inquisitive analytics that deal with different areas of analyzing data. Descriptive analytics is not to be confused with these though because they deal more with data after it has been organized and formatted. Descriptive analytics is the most important form of analysis when gathering business intelligence.
Descriptive analytics is very well described in an article by Bertolucci Big Data Analytics: Descriptive Vs. Predictive Vs. Prescriptive. Bertolucci defines descriptive analytics and its simplistic importance by saying “The purpose of descriptive analytics is to summarize what happened. Wu estimated that more than 80% of business analytics — most notably social analytics — are descriptive.” Not only is it the simplest but it is also the most basic and the other forms of analytics are vitally dependent on it. According to an article by Shankar V titled Business analytics driven students likings on social media there are many ways social media utilizes descriptive analytics. It is directly written “SNS contains exponential amount of user generated data which helps business analytics to analyze, summarize information for displaying proactive alerts in dashboards.” It gathers data through surveys or through monitoring habits of its users. Using this raw data, it can formulate specific advertisements for users that will appear on their webpages while they browse. It allows them a more responsive way to interact with users. It can also collect data on usage of certain web applications and can better help monitor for errors or malfunctions that could cause irritation for the user. Another article titled Big data in Government Services gives examples of how government agencies collect data and how they use it. The many uses include combatting terrorism and crime prevention by gathering data from convicts. “IBM has a big data analysis platform known as IMB Watson Foundation that has the capability to create solution of all data related to many government duties like threat prediction and protection, social program fraud, tax compliance, and crime prediction and prevention.” The IBM Watson Foundation provides a perfect example on what descriptive analytics can provide to the world. This massive collection of formulated data causes tremendous good, and it genuinely benefits the world.
Other forms of business intelligence are incredibly important, such as predictive analytics, inquisitive analytics, and prescriptive analytics. Each has an important part in gathering information for businesses, though they offer less importance in the big picture. Descriptive analytics allows businesses to firmly address the issues and the questions, and without a firm understanding other forms of analytics can do very little. It takes great understanding to make an informed decision and that is precisely what descriptive analytics specializes in.

Shankar, V. (2014). Business analytics driven students likings on social media. Advances in Management, 7(12), 22.


NoSQL {Comments Off on NoSQL}

By Jose Y.

The vast amounts of information that our devices are gathering and generating has paved the way for big data. Companies like google that receive extreme amounts of data or tech startups that does not need a full blown database solution has pushed for a non relational type of implementation. There are differences in schema, cost and data models between both types of database.


Big Data in Agriculture {Comments Off on Big Data in Agriculture}

By Michael W.

The influence of Big Data has been felt in a variety of fields, but there is one that most people wouldn’t initially think of and that is agriculture. The current trend of Big Data has had such a huge impact in agriculture that it even goes by a different name known as precision farming. In this process, “real time and historically generated data is collected in structured and unstructured datasets” (Bendre 2015). Farmers are well versed in knowing the several factors that can affect their crops and livestock from producing the best results possible, but there is only so much they can do within a given time. This is why the effect of gathering useful data and analyzing it through the assistance of Information and Communication Technology (ICT) is crucial to maintain efficiency. With the help of this not only will farmers be able to make smarter decisions on what their next course of action should be but also how they will “figure out how to feed the 9 billion people that will be on this planet by 2050” (Gilpin 2014). The old methods used in agriculture used thus far will not be enough to solve issues of the future.
The Indian company, Chitale Dairy, has gone a similar route by increasing the overall quality of milk production from their cows by having Radio Frequency Identification tags (RFID) placed on each cow to transmit information to the cloud and mobile devices. In order for farmers to do everything that is instructed correctly, “the farm then sends a to-do list to farmers in their local language each morning on what each cow needs based on the data collected from the RFID signals” (Horowitz 2015). The execution of this allows farmers to do everything needed which will also inform them of any warning signs a cow may give off indicating illness.
Despite the clear positives of Big Data’s use, there are many issues that result from it as well. As with anything else involving technology, maintaining security is one of the top priorities for farmers. By having so many devices with special sensors attached to the transferring data to its respective cloud, it runs the risk of having valuable information accessed from a threat. As stated by one farmer, “the overwhelming fear is that it falls into the wrong hands, be it a neighbor, a seed retailer, a fertilizer company, or a big agriculture corporation. And then that data is used against the farmer by being sold to a competitor or undercutting a neighbor for a better deal on land prices” (Gilpin 2014). Another issue that needs to be addressed is how ethics is involved. As Dennis Ludena has stated in his work, due to the recent popularity of Big Data, a significant amount of people haven’t fully grasped the consequences of showing only portions of data that looks pleasing to other individuals after “cleaning” the data sets.
Being at the forefront of creating a greater yield of products consistently has been the driving force of using Big Data today and it will only continue to grow from here. Even though there are some clear problems dealing with the use of this valuable information once it is obtained, I strongly feel that it is the right way to go about solving pressing issues in agriculture. With the help of this, there can be a way for farmers to have a greater output with the same amount or maybe even less input.


Big Data on Customers {Comments Off on Big Data on Customers}

By Kyle W.

Big data is becoming much more common and popular in many industries. The last decade has seen a huge increase in the amount of data that is continuously being generated and collected in a rapid rate, creating pressure among businesses to stay competitive that has amplified to a whole new level. Due to this, companies understand that customers can be assisted through big data analytics. Not only does Big Data help companies stay competitive, but it also helps create better customer relationships and experiences.


Databases and Technology in Politics {Comments Off on Databases and Technology in Politics}

By Tony W.

With the onset of the information age, databases and various sorts of technology have been playing a large role in politics around the world and in the United States. Nearly All successful political campaigns are using data in a meaningful way. Being able to understand it and take advantage of it can be the key to winning an election.


IoT Application and Analysis {Comments Off on IoT Application and Analysis}

By Jonathan Tr.

Technology today is growing faster than ever and improving the way we live in multiple ways. Cloud technology is now wirelessly collecting data from everyday physical objects embedded with sensors, chips, onboard computers, and so on. It’s changing the way we do habitual things like eat, sleep, and exercise while simultaneously collect and store all the data. Tech giants today like Google, Amazon, Microsoft, Cisco, IBM, Intel, and many more, are realizing the potential of this real time data and offer a variety of unique ways in processing all that raw data to turn into information for the rest of the world. One of the many problems with all this real-time data is how we can analyze this data to build IoT applications and benefit consumers and the industry.


The Quantified Self: Is Data good for your health? {Comments Off on The Quantified Self: Is Data good for your health?}

By Jonathan T.

In modern society, mobile technology has carved itself an integrated role in how we as a people recognize and process the enormous amount of data we encounter every day. Recording everything from data linked to when you last purchased a cup of coffee to something as specific as to which sites you enjoy browsing on Memorial Day, data on our activities and habits have become a valuable commodity. However, the rise of data-collecting and parsing technologies has also spurred a new movement which seeks to interpret self-generated data to better understand and learn about ourselves, known as the Quantified Self movement.