EDITOR ’ S QUESTION
TALAL SHAIKH , ASSOCIATE PROFESSOR & DIRECTOR ,
UNDERGRADUATE STUDIES , SCHOOL OF MATHEMATICAL AND
COMPUTER SCIENCES , HERIOT- WATT UNIVERSITY DUBAI
A great deal of a company ’ s decisions is now based on information collected from Big Data . Large corporations have a problem in that they handle a lot of data and it is a complex situation with data entering the system at variable speeds from various sources , requiring some decisions to be made on the fly . It is possible to use Big Data techniques in a variety of different contexts . Some of them are healthcare providers , especially those with multiple branches and larger hospitals , can use diagnostic data to pinpoint or predict illness and outbreak trends . Regular check-up data can also be used to understand public health trends , for example , herd immunity can be tracked or predicted based on diagnoses and check-ups from local health centres . This would also allow time to arrange supplies in time to cope with the shift in healthcare requirements .
Traditionally , businesses have used Big Data to analyse market trends and make strategic decisions in order to grow . During the on-going pandemic , for example , marketers are able to present customerspecific content when and where it was most effective to improve online and in-store brand recognition . Another great benefit of using Big Data for marketing purposes is to improve customer acquisition . Cloud computing permits the gathering and analysis of consistent and personalised data from multiple sources , such as web , mobile applications , email , live chat and even in-store interactions .
For storage and processing Big Data , two features are preferred : scalability and high-speed access to massive volumes of information .
It is possible for educators to track the performance of students using Big Data . Analysing a performance helps in understanding an individual ’ s and a collective ’ s performance . By analysing individual grades , educators can understand what students are most interested in .
With so many free tools available , it is not surprising that enterprises often get confused while selecting the best tool for data mining . A good place to start is open-source tools , since these are constantly being updated towards greater flexibility and efficiency by a large developer community . Most open-source data mining tools are similar to each other with some key distinctions . When selecting the best data mining tools , it is important to consider several factors such as type or format of data , size of data , objectives of data mining and the programmer ’ s preferred language ( Java vs R vs Python ).
For storage and processing Big Data , two features are preferred : scalability and high-speed access to massive volumes of information . Relational Database Management Systems ( DBMS ), whether centralised or distributed , are based on the use of SQL language and transactional properties that ensure atomicity , consistency , isolation , resiliency and durability ( ACID ) compliance . Massive Parallel Analytic Databases ( MPADs ) make up a significant part of relational database technology that is useful for Big Data . As opposed to traditional data warehouse , these DBMSs may implement large amounts of structured data with little to no data modelling and may scale up to multiple terabytes and petabytes .
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