Who Are We ?
DTscientist is creative, young & energetic team which uses data analysis & big data technique for business development & business efficiency purposes
Our focus in DTscientist is to analyze customer’s business in different perspectives by using new techniques based on data analysis and AI (Artificial Intelligence)
we seek to reach a complete and comprehensive analysis of businesses, which is useful and applicable.
What We Do . . .
Fundamentals
Data science is combined use of fundamental principles to support and guide the process of extracting information and knowledge from data. The application of data science can result in incredible insight and perception. Data science that we define in DTscientist is the unifier of statistics, data analysis, machine learning and other related methods, to reach a comprehensible understanding and analysis of actual phenomena with data.
Statistics
In order to reach a deeper & better perception of data science, statistics is used as prerequisite and is field of mathematics. Statistics is a large field including different findings & esoteric theories, but the nuts, bolts tools and notations are mainly needed in data science.
Professional Reports
Preparation of a professional report is one of our most important tasks.
Applicational Charts
An important parameter of charts for us is to be applicational.
Visuall Diagrams
We create visual diagrams for better understanding of results.
Usefull Tabels
One the most important part in statistics is to make useful tables of data.
Innovations
Big Projects
Action Plans
Great Tests
Programming
Since data science unifies statistics, data analysis, machine learning and other related methods, and these methods are very dependent on computer science and programming, data science and computer science are extremely connected. In DTscientist we use programming to enhance data science application.
Great Advices
We give you our advices based on our knowledge in data and business analysis.
24/7 Support
We provide fulltime support for your needs.
Optimal Choice
Wide range of choices are available for you
Clear Navigation
Navigation of the project is based on your business and your insight beside ours.
Machine Learning
Machine learning is the study of theories and technologies for adapting a system model with a training datasets in order to learned model will be able to generalize correct classification and useful guidance in new and unknown input. Machine learning foundation is built on linear algebra, statistical learning theory, pattern recognition and artificial intelligence.
Kung, S.Y., 2014. Kernel methods and machine learning. Cambridge University Press.
In DTscientist we gathered a great technical team for our high-tech data and business analysis
Market Analysis
We provide market analysis by machine learning in your businesses.
Financial Advise
We provide a package of financial experts and machine learning techniques to give you a financial advice.
Activity Analysis
We can analyze your business activities with machine learning techniques for your business growth.
Financial Tracking
Our machine learning techniques can be used for your businesses financial tracking.
Web Solution
Web is one of the ways for solving your businesses problems.
Financial History
Your business financial history is an important thing that can be described by machine learning
Big Data
We are living at the age of data explosion, and the term big data is often defined as enormous datasets.
Big data is masses of unstructured data which need more real-time analysis. Big data also brings about new opportunities for discovering new values and eras. It helps us to gain in-depth understanding of the hidden values, and also incurs new challenges such as an effective way to organize such datasets.
Chen, M., Mao, S. and Liu, Y., 2014. Big data: A survey. Mobile networks and applications, 19(2), pp.171-209.
In DTscientist we intend to use big data as a useful tool to analyze data and businesses toward our goals.
Data Ingestion
Data ingestion is to gather data from different sources into one place so you can see the big picture hidden in your data. In fact, the art of seeing all of your data as a single database is called data ingestion.
Beside other methods and techniques data ingestion is one of the most important tools we use in DTscientist’s data and business analysis projects.
Data Mining
Process of discovering patterns in large database with using a combination of machine learning, statistics and database systems is called data mining. Data mining’s goal is to achieve a comprehensible structure for further use of information.
Our team in DTscientist deeply believes in usage of data mining to achieve a comprehensible structure.
Data Visualization
Data visualization plays an important role in data analysis and data presentation. A good data visualization results in a good understanding and better analysis of the data and its use. Usage of new and innovative data visualizations methods that we apply to reports in DTscientist, results in a better perception.
fundamentals
Data science is combined use of fundamental principles to support and guide the process of extracting information & knowledge from data. The application of data science can result in incredible insight & perception. Data science is the unifier of statistics, data analysis, machine learning and other related methods, to reach understanding and analyzing of actual phenomena with data.
statistics
In order to reach a deeper & better perception of data science, statistics is used as prerequisite and is field of mathematics. Statistics is a large field including different findings & esoteric theories, but the nuts, bolts tools and notations are mainly needed in data science.
programming
Since data science unifies statistics, data analysis, machine learning & other related methods, and these methods are very dependent on computer science and programming Data science & computer science are extremely connected. programming is used to enhance data science application by involving computers.
machine learning
Machine learning is the study of theories & technologies for adapting a system model with a training datasets in order to learned model will be able to generalize correct classification & useful guidance in new & unknown input. Machine learning foundation is built on linear algebra, statistical learning theory, pattern recognition and artificial intelligence. Kung, S.Y., 2014. Kernel methods and machine learning. Cambridge University Press.
data visualization
Data visualization plays an important role in data analyze & display. A good data visualization results in a good understanding & better analyze of the data & its use. Usage of new & innovative data visualizations methods results in a better perception.
big data
We are living at the age data explosion, and the term big data is often defined as enormous datasets. Big data is masses of unstructured data which need more real-time analysis. Big data also brings about new opportunities for discovering new values &eras. It helps us to gain in-depth understanding of the hidden values, and also incurs new challenges such as an effective way to organize such datasets. Chen, M., Mao, S. and Liu, Y., 2014. Big data: A survey. Mobile networks and applications, 19(2), pp.171-209.
data ingestion
Data ingestion is to gather data from different sources into one place so you can see the big picture hidden in your data. In fact, the art of seeing all of your data as a single database is called data ingestion.
data munging
Data munging, also called as data wrangling, is the process of transforming and mapping data from "raw" data into another format to make it more appropriate and valuable for purposes such as analytics. Data Wrangling is not only about transforming and cleaning procedures. Many other aspects like data quality, merging of different sources, reproducible processes, and managing data provenance have to be considered. Endel, F. and Piringer, H., 2015. Data Wrangling: Making data useful again. IFAC-PapersOnLine, 48(1), pp.111-112.
Our Clients
