Shingirayi Mandebvu's Blog

Why Data Science? We want to be an AI driven organisation but in order for that we need to be a data driven organisation. It helps make better decisions (Scientific Method) It helps with making smarter products Automating Manual Methods This is the process of converting data to knowledge. Common sources of data being big data database systems like Spark, MongoDB and Excel. Process of turning your organisation to a data driven organisation Find a question Collect Data Process (munch) the data Create a model Evaluate the model Deploy Repeat (if necesary) Key components for a data driven organisation Strategy People Data Technology Culture The data science hierarchy of needs 

Why database I know a quick google on the definition of database will yield results suck as a repository of information   but what my tutor taught me is that that definition is akin to defining an engine as a collection of metal parts. So the definition must now be more inclined towards why database. Because database is more than just storing information (because whats the point when you can simply store the information on an excel spreadsheet. Why database then? Its because of what happens next. Imagine these scenarios (which are perfectly normal when it comes to real world scenarios) Data Grows Changes over time - and we need to be able to track the changes Should be fast and searchable Should have awesome up-time and be interdependent to other systems should be consistent and protected (secure) So why database is to be able to solve all the problems that come with data. It is to provide a more organized repository of information.  Relational Database manageme

How it began To me the concept of cloud started when people began virtualizing their systems using the like of Virtual-box and VMware. What bough this a;long was the evolution/advent of technology which made it possible for software so simulate hardware. Originally software could not simulate hardware drivers but the moment that became possible- virtualization was born. A few years after- companies started offering this virtualization at a much grander scale and Infrastructure as a service was born. Lets get down to the three cloud components namely: Infrastructure as a Service (IAAS) This outsourced hardware meaning that one noways noes not need to setup servers, air-con and the like of access control but could 'rent' from someone and one of the great things about this was that a backup not only meant software but also meant hardware (as software could now simulate hardware) so recovery in case of disaster became easier. Platform as a Service (PAAS) This is

Library: Lets take for example. You write code that prints Hello World to the screen. Someone refines it and maybe it starts to ask input before printing. Someone again adds different text formatting to it and you no longer need to rewrite the same code ever again to achieve that functionality. Framework: Imagine you are builing a house. and you get a system that provides the scafflolding, foundation and the frame at the same time so that you don't need to redo most of the work. This is like a library on a grander scale- flexibility/functionality is reduced. SDK: In the old days - one would get a software development kit (something like pictured below). But it would be filled with floppy disks, documentation books etc. So it was an actual kit! Class: This is a template\blueprint or a recipe list.

Times have changed. We moved from making fire with sticks to amazing things like 3d printing, biotechnology, block-chain and artificial intelligence. No doubt- we are only starting. But one thing is of worry- how we learn. Learning can be subdivided into 4 parts(in the particular order) namely: Fundamentals Information Skills Innovation These can be applied to the Technology, Business and Finance and the Leadership and Management branches. The main goal nowadays is not to be an expert if you want to quickly build your career and make some money in the process. The main aim for now is to gain competence. Why I say that is because it is cheaper for an organisation to get someone with competence as opposed to getting an expert. The most efficient way is to aim for the skill level as opposed to the expert level(which tends to come by itself as you sharpen the skills level) We want to maximize financial benefit from the most efficient way possible. 1. Fundamentals Fundamental