The welcome party recap Pt 1. So, for the sake of community member…
By: Temidayo Adeniyi
Tags: Analytics, Big Data, Data Analysis, Data Science, Statistics

So, for the sake of community member that were not able to join the welcome party due one or two busy schedule or funny enough the connections(internet connection, you know), Here is a recap of what was covered and discuss in the welcome party, sit back, grab your pen and paper or stick note whichever way you want to put it and enjoy a recap.

Okay, It is our first meetup and it is tagged Welcome Party.

Prior to this participant (interested community members) already opt-in and an email detailing the rules and guide were sent out and the next line of action was also stated, and from the moment the email got delivered, participant are onboarding to the community with the next steps as highlighted in the email.

The D-day later comes and all ready for the real welcome party.

The party as fondly called commenced with the Lead, Adeniyi Temidayo welcome everybody, do some basic house rule, then highlight the agenda of the day, thus:

i. Basic guideline

ii. Introduction of the community leads

iii. A brief introduction of the community

iv. Some background development trend and evolvement

v. clarity on some evolved buzzwords

vi. Duties and what to expect going forward.

I. Basic Guideline

Then the guide serves as the outline that helps in handling and moderates the party.

Adeniyi Temidayo relay the guideline, rules and regulation that will help put things in other in the community and things under check too.

Part of the expectation of what the community aim to achieve given thus,

Participants will be given access to good/best learning resources/material to help them understands the convergent area of data science and its technological implementation.

Here are some housekeeping rules & guidelines, it also serves as an introductory note as well.

Do your best to abide by these rules.

And then this is further reiterate thus,

We will have an hour for the session, 30min(clarification and Feedback) for the first day and an hour(Q&A, Comments and Discussions).

Follow us via our social media handle.

Schedule: Wednesday 5 pm and Saturday at 5 pm.

Once again if you do have questions ahead of the day assigned for Question and Answer and you do not want to forget or have the privilege to jot it down, send to our DM or you tweet at us via twitter(@ds4africa).

II. Introduction of the Community Leads

The community leads were introduced one after another, thus Jolayemi Olubunmi, Joshua and oni Stephen and quickly add that they are ready and willingly drive the community and provide support all the way and across the board as regards the community.

III. A brief introduction of the community:

Over time we have heard of various different buzzwords around data which range from AI, ML, Neural network, and all sort, but then very few people know the meaning of these buzzwords and very very few people know the real major role that buzzword plays, hence, the need to go to the very root of all of these buzzwords and get the clearer picture and be knowledgeable about them, hence, the very need to start at the very basic of it all. in the course of the session, some things we experience daily and how those buzzwords play a role in them will be made clear without forgetting that we connect with them all along.

We are the very person that can proffer a solution to our problem simply because we understand the problem better, and in other to do that we need to understand what tools can help in achieving this, and with the advent of technology some of the processes can as well be automated, so why not learn the tools and tech that can be used to achieved solution and leads more progress.

These we deem fit to know and get clear and not waiting for the foreigner to come to explore our land simply because they have the right tool and are knowledgeable about it uses, then applying it on our raw materials. To not waste much time on this, the community is set to go from the very beginning and that is why you solve the basic mathematics to get everybody along, which means to a certain level we will have to solve some basics maths and take it up from their to how they apply and their application in our daily activities. several daily challenges that can be resolved will as well be highlighted and treated as a community because some of the solutions might be open-sourced too from our end and share with others to explore.

IV. Some background development and evolvement:

some 25yrs ago we have a job role of Statistician saddle with the responsibility of

(i) Gathering of data and cleaning of the same data and

(ii) Applying statistical methods.

But as data growth evolves plus radical tech improvement 5yrs down the lane (20yrs now) we then have the job role changed to Data Mining these with the former job role then combine with extracting pattern from the data collected and thus it helps to make more accurate forecast, moving forward to 10yrs ahead which in addition to the evolvement of duties and tech improvement and data growth from data mining then, we now have Predictive Analytic Specialist that now add new mathematical and statistical method on the same data and the growth of it, hence, the new job role: Data Scientist while things still evolve and radical improvement of technology which happens drastically fast then the need for AI(Artificial Intelligent), Machine Learning (which aside pattern deals with modelling), and more and more… more light will be shed on some of these in details in the cause of subsequent meetups.

Lets quickly add that meetup will go virtual for a while and when there is a need for a physical meetup you all will be informed ahead and for now we will remain virtual and keep to schedule.

V: Clarity on some evolved buzzword:

Due to time this section was limited this to these two words that are interchangeably used Analytics and Analysis these words are used in their literal English meaning but when it comes to the world of Data, which then becomes Data Analytics and Data Analysis they play distinctly different roles and in different spheres, lets touch a few areas on this.

Remember we collect data, which can be simply named, age, gender, level, grade, or even from hospital blood groups, rhesus, or in the banking industries, demographics, and cut across different industries with a different set of datasets.

These data that were collected can be Analyze (Analysis) since they are very large, by splitting them into different smaller chunk and study separately. these simply makes it clear that Analysis has to do with a past event which helps us to collect the data, and from the studying of the data we can be able to explain WHY there is a surge in admission in a certain year, why the rate of male applying for engineering reduced in the recent year, why the male gender are moving into banking and finance as a course, why banks are rolling out different saving plans for the teenagers, and as well explain HOW it all happens that way due to the outcome of the study of data collected.

Summary:

Analysis relies on past events (Data of event that happened), a study in chunks and helps in explaining the WHY it happens and How it happens

Been conscious of time and considering other participants to quickly catches up when they come online, He quickly then wraps up with the Analytic part, Analytics, he then explains that it deals with the future exploration of potential events or put this way, Analytics explore future potentials based on the pattern observed from Analysis. Analytics also make use of the application of logical and components parts which is obtained in analysis, which means we have to have good reasoning in interpreting the outcome of the analysis, look for patterns that can be explored in future. if time permits in the next session we will look into the Qualitative and Quantitative aspect.

To also ensure that participants were following and if it worth the time, He then asked if the participants gain something in this intro party? Then ask for feedback from the active participants to rate the session and in his word the way he puts it.

Rate this session on a scale of 5 (1 not what I expect at all while 5 it worth it and more of such am expecting)? let quickly give a response to this in the next 2min.