Definition of Big Data

Big Data is a phrase used to mean a massive volume of both structured and unstructured data that is so large it is difficult to process using traditional database and software techniques. In most enterprise scenarios the volume of data is too big or it moves too fast or it exceeds current processing capacity. Big […]

Historical Development of Big Data

90% of the available data has been created in the last few years and the term Big Data has been around 2005, when it was launched by O’Reilly Media in 2005. However, the usage of Big Data and the need to understand all available data has been around much longer. In fact, the earliest records […]

Growth of data (including measures of data)

Big data is defined by large quantities of data. There isn’t an exact unit of measurement to classify what is or isn’t big data, but this is somewhat intentional. The “quantity” of data, as it relates to big data, isn’t solely dependent on the shear volume or size of the data – big data also […]

Reasons for the growth of data

In general, the following information infrastructureindicators can be used to assess the factors affecting thegrowth and development of Big Data: A number of Internet users; Worldwide per capita information; A number of devices connected to the Internet; A number of mobile devices connected to the Internet; A number of mobile phone users; A number of […]

Value of data (including future value)

Data seems to be on everybody’s lips these days. People are generating more than ever before, with 40 zettabytes expected to be created by 2020. It doesn’t matter if you are selling to other businesses or ordinary members of the general public. Data is essential for companies and it’s going to spell an era of […]

Traditional statistics (descriptive and inferential).

  D Inferential Statistics Inferential statistics involves studying a sample of data; the term implies that information has to be inferred from the presented data. A sample of the data is considered, studied, and analyzed. Unlike descriptive statistics, this data analysis can extend to a similar larger group and can be visually represented by means […]

Limitations of traditional data analysis.

The important limitations of statistics are: Statistics laws are true on average. Statistics are aggregates of facts, so a single observation is not a statistic. Statistics deal with groups and aggregates only. Statistical methods are best applicable to quantitative data. Statistics cannot be applied to heterogeneous data. If sufficient care is not exercised in collecting, […]

Characteristics of big data analysis

Big data analysis has gotten a lot of hype recently, and for good reason. You will need to know the characteristics of big data analysis if you want to be a part of this movement. Companies know that something is out there, but until recently, have not been able to mine it. This pushing the […]

Future applications of big data

The availability of data, a new generation of technology, and a cultural shift toward data-driven decision making continue to drive demand for big data and analytics technology and services. Over the past 15 years, enterprises have continually invested in data warehouses, data lakes, data marts, and now the cloud—all with the hope of gaining integrated […]

Technological requirements of big data

Big data isn’t just data growth, nor is it a single technology; rather, it’s a set of processes and technologies that can crunch through substantial data sets quickly to make complex, often real-time decisions. Advances in computing tend to focus on software: the flashy apps and programs that can track the health of people and […]

Limitations of predictive analytics

The evolving technology of Predictive Analytics is opening new possibilities for predicting future events by studying past performance. Now that Big Data enables Data Scientists to review massive amounts of data, users can hope that the degree of accuracy in future predictions will only rise. As with many aspects of any business system, data is […]

Strategies for limiting the negative effects of big data

Under the EU General Data Protection Regulation (GDPR), all organizations – whether within or outside the EU – need to obtain EU residents’ consent to store or process their personal data, maintain “Privacy by Design,” and respond quickly to their “subject access” and “right to be forgotten” requests. The General Data Protection Regulation (GDPR) sets […]

Types of problem suited to big data analysis

Big Data: the most overused and ill-defined buzzword in business today. Companies are investing time, money and valuable resources behind their efforts to be more data driven. But, is bigger data always better data? The benefits of data are widespread. It helps businesses understand their customers – who they are, their shopping habits, and their […]

Data mining methods

Data mining is the process of sorting through large data sets to identify patterns and establish relationships to solve problems through data analysis. Data mining tools allow enterprises to predict future trends. In data mining, association rules are created by anIn data mining, association rules are created by analyzing data for frequent if/then patterns, then […]

Types of visualization

Big data visualization refers to the implementation of more contemporary visualization techniques to illustrate the relationships within data. Visualization tactics include applications that can display real-time changes and more illustrative graphics, thus going beyond pie, bar and other charts. The mind processes visuals more efficiently and effectively than words Data visualisation is essentially quicker and […]

Application of big data techniques

Unemployment rate (Annual) in UK — Visible increase after the Global Crisis of 2008 Unemployment rate (Annual) in UK, female —- there is an interesting difference in data from Northern Ireland Unemployment rate (Annual) in UK, male —- no difference in data from Northern Ireland Unemployment rate (Annual) in UK —- different types of visualisation