DATA ANALYST

DATA ANALYST & SCIENTIST

    

zahi@hackon:~$ sudo Sahith

Hi, I'm   Sarbudeen Mohamed Sahith.

Bachelor of Science - B.Sc. in Applied Sciences (Computer Science, Chemistry, Applied Statistics)
South Eastern University of SriLanka.

I'm a consultant that provides of data analyst & statistics

assessments services for a variety of industries.

Basically, I analysis into companies to show the techniques adversaries use!

My professional interests:
•	Math (statistics and probability)
•	Logic and analysis.
•	Relational databases (MySQL)
•	Problem-solving and troubleshooting.
•	Pattern and trend identification.
•	Data mining and data QA.
•	Database design and management.
•	SharePoint and advanced Microsoft Excel functions.
•	Tableau and Qlik
•	Business intelligence (BI)
•	Programming languages (python,PHP,HTML)
•	Risk management
•	System administration
•	Quantitative methods
•	Data warehousing
•	Regression analysis
•	Data science research methods
•	Experimental design & analysis
•	Tech support
•	Survey creation
•	Collecting, collating and carrying out complex data analysis in support of management & customer requests. Also involved in reporting statistical findings to work colleagues and senior managers.
•	assisted with the creation of a new customer database that compiled shopping data to generate
•	Analysing raw data, drawing conclusions & developing recommendations
•	Writing T-SQL scripts to manipulate data for data loads and extracts.
•	Developing data analytical databases from complex financial source data.
•	Performing daily system checks.
•	Data entry, data auditing, creating data reports & monitoring all data for accuracy.
•	Designing, developing and implementing new functionality.
•	Monitoring the automated loading processes.
•	Advising on the suitability of methodologies and suggesting improvements.
•	Carrying out specified data processing and statistical techniques.
•	Supplying qualitative and quantitative data to colleagues & clients.
•	Using Informatica & SAS to extract, transform & load source data from transaction systems.
•	Data entry, data auditing, creating data reports & monitoring all data for accuracy.
•	Designing, developing and implementing new functionality.
•	Monitoring the automated loading processes.
•	Advising on the suitability of methodologies and suggesting improvements.
•	Carrying out specified data processing and statistical techniques.
•	Supplying qualitative and quantitative data to colleagues & clients.
•	Using Informatica & SAS to extract, transform & load source data from transaction systems.
•	Data entry, data auditing, creating data reports & monitoring all data for accuracy.
•	Designing, developing and implementing new functionality.
•	Monitoring the automated loading processes.
•	Advising on the suitability of methodologies and suggesting improvements.
•	Carrying out specified data processing and statistical techniques.
•	Supplying qualitative and quantitative data to colleagues & clients.
•	Using Informatica & SAS to extract, transform & load source data from transaction systems.

- Basic scripting in Python, Java Script, PHP,
SQL, C,C++ , BASH .

What do they do?

One of the biggest differences between data analysts and scientists is what they do with data. 

Data analysts typically work with structured data to solve tangible business problems using tools like SQL, R or Python programming languages, data visualization software, and statistical analysis. Common tasks for a data analyst might include:

• Collaborating with organizational leaders to identify informational needs

• Acquiring data from primary and secondary sources

• Cleaning and reorganizing data for analysis

• Analyzing data sets to spot trends and patterns that can be translated into actionable insights

• Presenting findings in an easy-to-understand way to inform data-driven decisions

Data scientists often deal with the unknown by using more advanced data techniques to make predictions about the future. They might automate their own machine learning algorithms or design predictive modeling processes that can handle both structured and unstructured data. This role is generally considered a more advanced version of a data analyst. Some day-to-day tasks might include:

• Gathering, cleaning, and processing raw data

• Designing predictive models and machine learning algorithms to mine big data sets

• Developing tools and processes to monitor and analyze data accuracy

• Building data visualization tools, dashboards, and reports

• Writing programs to automate data collection and processing