6. Traditional statistics

Traditional Statistics is simply the act of gathering data and searching for trends among it. It is widely used in many different ways in our society.

Medical uses could be for vaccines, as doctors can recover results information from different types of vaccine for a disease to insure safety when administering it to large amounts of people

Communication companies also use statistics to help identify faults within the network so that they can be fixed faster which in term ensures that customers will be able to regain full functionality in a shorter time

Government agencies around the world rely on statistics for a clear understanding of their countries, their businesses and their people.

Comments

7. Limitations of traditional data analysis

7. Limitations of traditional data analysis Security: Security is foremost aspect for every technology. Big data is prone to data breaches. The important information that is provided to some third party may get leaked to customers. Proper encryption must be made in order to protect the data. Large growth in data : data is growing faster than the processing power. Large volumes of data are being exploded in past years. We need some new machines to work; otherwise we will get over run by data. Large Data centres can solve this problem. Inconsistencies: Sometimes the tools we use to gather big data sets are imprecise. This will happen when the data is collecting for example, consider Google search Edinburgh College results of the search on one day will be different from other day, this is mainly due to inconsistency in data collection.

3. Growth of Big Data

3. Growth of Big Data Kryder's law - The idea that data storage will double almost every year (13 months), as the storage capacity increases, storage will decrease in price. https://searchstorage.techtarget.com/definition/Kryders-Law growth of data - Data is increasing at an exponential rate, more data has been made in the past two years than ever before combined. It is estimated that by the year 2020, 1.7MB of new data will be made every second for every human on earth. Within 5 years there will be 50 billion smart connected devices on earth. also by 2020, at least 1/3 of all the world's data will pass through the cloud. The image below contains more examples of data growth as well as a graph for visual representation https://dvmobile.io/dvmobile-blog/feeling-overwhelmed-by-a-deluge-of-iot-data-iot-data-analytics-dashboards-can-help

2. Historical development of Big Data

2. Historical development of Big Data 1980's - networks started to appear across other countries, although possible, connection was still extremely difficult without travelling, the networks had to communicate in the same language as opposed to different ones. The principle link at CERN connected the US and Europe in 1989 1990's - remote access of data in the terabytes was now easily achievable around the world. To share data more easily, the web was created so that the actually location of the data wasn't necessary to know 2000's - Big data was now so large that CERN was unable to store such a vast amount of petabytes themselves and as such had to share it between partners around the world to offload some of it. This lead to the creation of cloud computing 2005 - The term Big Data is used for the first time by Roger Mougalas, a year after the creation of the term "web 2.0" which refers to data too large to handle with traditional business methods 2009 -...

Big Data EC1702991

Search This Blog