Notes

Information ALL 2018 seminar with the theme "Be Amazed with Data Science" with several speakers, that is:
1. Bapak Afif Akbar Iskandar, S.Si, M.Kom as AI in Bukalapak
2. Dr. Bapak Taufik Edy Susanto, MscTech as Applied Mathematics, Data Science, IoT & Big Data. Also work Lecturer of Mathematic in UIN Syarif Hidayatullah
3. Bapak Nugroho Budi Wicaksono as Chief Technology Officer (CTO) in Emago.

On my resume this time describes Data Science and Big Data that I wrote when he explained. Then what is Data Science? Here I can conclude that Data Science is explained by speaker 1 that is by Mr. Afif Akbar Iskandar, then Data Science is “A data scientist is someone who is better at statistics than any software engineer and better at software engineering than any statistician.” –John Wills

Speaker 1: Mr. Afif Akbar Iskandar, S.Si, M.Kom

There are many benefits and functions of Data Science, among others in the field of business to predict products, place two or more different products or market basketball analysis or complete the Algorithm data.

From his explanation that in a data science project involves various elements, as for concepts and combinations that facilitate organizations to manage and maintain historical data obtained from systems or operational applications. That is, Develoment Data of Insight can be concluded as a decision, then Develoment Data of Product can be concluded as a result of inflomen, a product such as a gadget.

To become a Data Science we must have skills, that is a Mathematics & Statistics Expavtise, Technology - hacking Skill, Business / Acumen Strategy.
Math & Stact consists of Statistics, Calculus, Probability, and Linear Algebra. Tech - Hacking consists of Data Store, Transtrom, Model, Visualize, and Other Tools.

There is also an explanation from Machine Learning and Data Science. Machine Learning is part of AI (Artificial Intelligence) and Data Science that is Machine Learning products usually with Real.

Then what is Big Data? From what I have gained, that is the activity of collecting large datasets that can come from digital and traditional sources to identify certain trends and patterns.

From his explanation, big data has 3 characters that is, Volume, Velocity, and Variety. Whereas for Big Data processing there are 5 characters that is, Volume (Data size), Velocity (speed of data generated), Variety, Data Veracity, and Value.

There is also an explanation from him regarding Deep Learning. Deep Learning or DL which means Successive Layers of Representations or commonly called Layered Representations.

Speaker 3: Mr. Nugroho Budi Wicaksono

From his explanation, it can be concluded about Collect Task Breakdown which consists of several, namely Data Architecture Management, Meta Data (Give Data More of Contect), Reference & Master, Document & Content (Create Lodigical), Data Security, Data Develoment (Guards data store from undersired value), Database Operation (Encapsulates multiple operations with transactions, Only soft delete records, and Create a Retry / Circuit Breaker / Timeout / Buikhead Insolation), Instrumentation, and Logging (Make a structure for log data, Compartmentalize sensitive data, and Available tools to store log data: Elasticsearch).

There is also a level that is in Log (Cont.) That is Critial (5), Debug (1) that is Information that is diagnostically helpful to people more than just developers, Error (4) that is Any error which is fatal to the operation, but not the service or application, Information (2) Generally useful information to log, None (6), Trace (0), and Warning (3).