Data Analytics: - What’s Data Analytics

Over the years, “Big Data” become one of the hottest topics.  For most of the people, I think the most common question would be “What Big Data is?” and my answer would generally be it’s about analyzing huge amount of data which, it implies that it’s not only “Data”, but “BIG" data indeed. And to certain extent, it’s in fact about producing insights which stimulate your further thinking; options and suggestions for the purpose of making decisions; and finally presenting the fact to improve your understandings.

Another common question is “Do Data Analytics help? And is it useful?” and my answer would be “Yes or No, it’s depends on you”.  I am not trying to trick the questioners, but my thought is that before telling whether Data Analytics helps, you should ask yourself whether you believe in this and what you wants to achieve. It’s like religion, the results sometimes not explainable at all and it’s just about whether you believe or not.  If you believe in it, it would help to make your life easier in some circumstances and, at least, it helps to justify your decision or proof your thoughts.  However, please ensure that you aware Data Analytics for decision any purpose is usually based on only what happened historically only.  If you are looking for prediction, one of the simplest caveats is that future is full of surprise as always.

We should consider Data Analytics as our right hand man who give insights, options and suggestions to make our life easier where we are still the actual decision makers ultimately.  It is always about how you control the tools but not the tools control you.  

From my experience, most people, who dare to believe in data, always said that they would more believe in “experience” bit not figures.  However, my thought is that believing in experience OR Data Analytics are basically following the same logic.  Data Analytics, from my point of view, is to analyze historical data resulting in something useful for decision making or understand the fact.  The way of how’s human brain works on “experience” is somehow similar to how Data Analytics works on “historical data” but human brain is actually much powerful indeed.  Recently some researchers just took 40 minutes with 83K processors in K computers to get 1 second of biological brain processing time where my laptop is using quad-core processors i.e. 4 processors. 

In the view of the management level, there are just thousands of ways to conduct Data Analytics OR leveraging the concept of Big Data.  The most important would be how you implement and manage it into your business, such as the Analytics Cycle which I planned to discuss in the next Data Analytics post…
 

My first post: - Introduction

conceptual structure of my focus areas

As for my first post, let me start with some quick explanation on what’s Computer Forensic, e-Discovery and Data Analytics is according to my own understanding and interpretation.

 

I am a Chinese who born in British Hong Kong. My mother-tongue is Cantonese where English is one of my second languages.  However, be honest, I am an idiot in Chinese character typing so that this blog is going to be conducted in English and I think people interested in my focuses do have a common language in English. 
 

Please kindly forgive me if you found any silly grammatical mistake here and please just feel free to clarify with me if any of my words are misunderstanding or misleading.  All the things in this blog are purely based on my own experience so please allow me to place my very first caveat here that the information provided in this blog may not happened the same in your scenarios where I do believe that there are always much more to explore and to learn in the reality.

 

Computer Forensic: - general speaking, it’s about investigating and presenting on what the users did on any of his digital devices including, but not limited to, desktop, laptop, external hard disk, USB thumb drive, smart phone, etc.  Computer Forensic experts are acting as a storyteller who present the fact.  We are not magician or superman with superpower, so that all our analysis or works are always technically limited by the available technology sciences.  The most common tasks are data preservation, data recovery, system log analysis, etc.  In additional to dealing with the technical supports, unlikely ordinary IT people, computer forensic experts also required to have certain legal knowledge and presentation skill to act as the storyteller in the Court or towards the clients.

 

e-Discovery: - It’s a legal terms from US originally.  It’s about discovery in litigation or regulatory requested investigations on the electronic stored information (ESI).  Over 70% of works are relied on the software which allows us to do indexing, keyword search, and some other analytics on the backend; then allows the investigators, such as forensic accountant, lawyer, law enforcement officer, etc. to review the information with an auditable and forensic sounded process from the frontend.  The rest 30% are relied on the analysts’ experience while there are always sometimes tricky step which enable the data access towards the actual data content, such as encrypted data, email archive, OCR, etc. and to make the review process more effective and efficient. 

Data Analytics: - As from the words itself, this is to analyze the data according to the business needs.  It’s not only about investigation but could also in any forensic or non-forensic needs.  It could be for business review, management consulting, academic research, personal interest, etc. which is a very hot topic today namely “Big Data”.  Data Analytics has generally no limit on work scope range from purely data entry and consolidation, system and data integration, business restructuring, user interface design, to management decision making, etc. This almost 90% relies on the data experts’ experience and innovations to identify the right most solutions task by task.