I graduated the Marmara University in 2018 and hold a Bachelor’s degree in Chemical Engineering. After getting my BSc, I worked as Supply Planning Engineer in a food solution company DöhlerGroup for 2 years. In June 2020, I attended the Data Science Program at UP School for 18 weeks. After completing the program, I started to work as a Business Analytics Specialist at Smartech Information Technologies. At present, I work on Microstrategy and give consultancy Eczacıbaşı Information and Communication Technologies. Then, I decided to extend more my knowledge to accomplish career goals about Big Data Analytics.
My interest in technology and science has begun when I was in high school. I was curious about the relationship between nature and mathematics. Therefore, I decided to study engineering. In my college years, I have interested in computer programming lectures. It was very impressive to be able to produce something by coding. Also, it was like the game solving algorithm problems. Then, in my second year, I joined the Engineering Faculty of Robotic Team. I realized that I was eager to learn software-related fields more than Chemical Engineering. While I was seeking career opportunities in this field, I was interested in data because data touch everywhere. It is an interdisciplinary field and business knowledge is one of the important skills. Accordingly, I decided to work in this field would be suitable for me.
After my graduation firstly, I wanted to gain work experience to improve my business and management skills. I chose to work in the Supply Chain department because it improves both operational management skills and has several data-based projects as demand forecast, process mining, SAP IBP etc. So, I started to work as Supply Planning Engineer. I did two projects as Recipe (Bill of Materials) Optimization and Sales Forecast. In addition, I participated SAP Implementation Project. In this way, I was involved in a digitization project and saw all the processes. Then, I came across the Data Science Program organized by UP School. The program lasts 18 weeks and offers job opportunities in Data Science to those who successfully graduate. I applied to this program and was entitled to receive training. Along with the program, we received several basic trainings in Data Science and related fields.
After all my experiences, my interest in data analytics has more increased. I think it is a field that shapes the future through the decision support systems created by managing and making sense of complex data. I haven’t chosen a specific field that will shape my career yet. My first goal is being professional about fundemantals subject in this field and explore the field that suits my ability and interest.
In recent years, environment problems dragmatically increasing. The scientists more monitor and research environmental changes. I think, data analysis and make sense of data are one of the important step. I want to share The Session Ecology and Environment. The first part of session presented by Timofey Samsanov who Research Scientist in Lomonosov Moscow State University. He talked about the grwat R package he developed with his teammates. grwat is the abbreviation for Ground Water. grwat is being developed for automatic analysis and separation hydrograph. The river hydrograph is one of the most important characteristics of river discharge. Mainly the package automates the routine operations that raise during the analysis of river hydrograph Also, it provides the specialist with a useful tool to compare the changes in river hydrograph and climatic changes to provide the statistical tests that how significant these changes are.
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This technical note is about how to operate a data-driven decision-making model in financial risk cases in the bank sector. The Single Resolution Board (SRB) is the central resolution authority within the Banking Union, which at present is 19 eurozone countries, Bulgaria and Croatia. Its mission is to ensure an orderly resolution of failing banks, protecting the taxpayer from state bail-outs, which is promoting financial stability. There are 4 significant parameters for model that correct, reliable, reproducible and auditable. The SRB uses RStudio Teams deployment, consisting of RStudio Workbench, RStudio Connect, and RStudio Package Manager. By means of R, the SRB is able to deploy high-quality models and data pipelines while at the same time reducing lead times.
Time series is an ordered sequence of values of a variable at equally spaced time intervals. Time Series Analysis is used for many applications like forecasting, process and quality control, inventory analysis etc. A time series has 4 components level, trend, seasonality and noise. Also, there are many time series modelling techniques. Some of these are Averaging Methods, Exponential Smoothing Techniques. In this tutorial, time series analysis of passengers will be done by using time series functions in R.
Recommendation systems have an important role, especially, in the e-commerce sector. Making recommend the right product to the user increases satisfaction, sales volumes and average time on pageor app. There are two main methods as content based and collaborative filtering. This tutorial shows step-by-step recommendation system by using R package recosystem.