Role proficiency:
independently provides expertise on data analysis techniques using software tools; streamlining business processes and managing team
outcomes:
- managing and designing the reporting environment including data sources security and metadata.
- providing technical expertise on data storage structures data mining and data cleansing.
- supporting the data warehouse in identifying and revising reporting requirements.
- supporting initiatives for data integrity and normalization.
- assessing tests and implementing new or upgraded software and assisting with strategic decisions on new systems.
- synthesize both quantitative and qualitative data into insights
- generating reports from single or multiple systems.
- troubleshooting the reporting database environment and reports.
- understanding business requirements and translating it into executable steps for the team members.
- identify and recommend new ways to streamline business processes
- illustrates data graphically and translates complex findings into written text.
- locating results to help the clients make better decisions.
get feedback from clients and offer to build solutions based on the feedback.
- review the team's deliverables before sending final reports to stakeholders.
- support cross-functional teams with data reports and insights on data.
- training end users on new reports and dashboards.
- set fast goals and provide feedback on fast goals of reportees
measures of outcomes:
- quality - number of review comments on codes written
- accountable for data consistency and data quality.
- illustrates data graphically and translates complex findings into written text.
- number of results located to help clients make informed decisions.
- attention to detail and level of accuracy.
- number of business processes changed due to vital analysis.
- number of business intelligent dashboards developed
- number of productivity standards defined for project
- manage team members and review the tasks submitted by team members
- number of mandatory trainings completed
outputs expected:
determine specific data needs:
- work with departmental managers to outline the specific data needs for each business method analysis project
management and strategy:
- oversees the activities of analyst personnel and ensures the efficient execution of their duties.
critical business insights:
- mines the business's database in search of critical business insights and communicates findings to the relevant departments.
code:
- creates efficient and reusable sql code meant for the improvement
manipulation
and analysis of data.
- creates efficient and reusable code.
follows coding best practices.
create/validate data models:
- builds statistical models; diagnoses
validates
and improves the performance of these models over time.
predictive analytics:
- seeks to determine likely outcomes by detecting tendencies in descriptive and diagnostic analysis
prescriptive analytics:
- attempts to identify what business action to take
code versioning:
- organize and manage the changes and revisions to code.
use a version control tool like git
bitbucket.
etc.
create reports:
- create reports depicting the trends and behaviours from the analysed data
document:
- create documentation for own work as well as perform peer review of documentation of others' work
manage knowledge:
- consume and contribute to project related documents
share point
libraries and client universities
status reporting:
- report status of tasks assigned
- comply to project related reporting standards/process
skill examples:
- analytical skills: ability to work with large amounts of data: facts figures and number crunching.
- communication skills: communicate effectively with a diverse population at various organization levels with the right level of detail.
- critical thinking: data analysts must look at the numbers trends and data and come to new conclusions based on the findings.
- presentation skills - reports and oral presentations to client
- strong meeting facilitation skills as well as presentation skills.
- attention to detail: making sure to be vigilant in the analysis to come to correct conclusions.
- mathematical skills to estimate numerical data.
- work in a team environment
- proactively ask for and offer help
knowledge examples:
- database languages such as sql
- programming language such as r or python
- analytical tools and languages such as sas & mahout.
- proficiency in matlab.
- data visualization software such as tableau or qlik or power bi.
- proficient in mathematics and calculations.
- spreadsheet tools such as microsoft excel or google sheets
- dbms
- operating systems and software platforms
- knowledge about customer domain and also sub domain where problem is solved
additional comments:
- hands on administration of database administration - kknowledge in rdbms concepts / administration / migration on cloud and non cloud vice versa.
- expertise the d