1. What is the average salary of a Data Modeling Analyst, Sr.?
The average annual salary of Data Modeling Analyst, Sr. is $124,944.
In case you are finding an easy salary calculator,
the average hourly pay of Data Modeling Analyst, Sr. is $60;
the average weekly pay of Data Modeling Analyst, Sr. is $2,403;
the average monthly pay of Data Modeling Analyst, Sr. is $10,412.
2. Where can a Data Modeling Analyst, Sr. earn the most?
A Data Modeling Analyst, Sr.'s earning potential can vary widely depending on several factors, including location, industry, experience, education, and the specific employer.
According to the latest salary data by Salary.com, a Data Modeling Analyst, Sr. earns the most in San Jose, CA, where the annual salary of a Data Modeling Analyst, Sr. is $156,805.
3. What is the highest pay for Data Modeling Analyst, Sr.?
The highest pay for Data Modeling Analyst, Sr. is $153,792.
4. What is the lowest pay for Data Modeling Analyst, Sr.?
The lowest pay for Data Modeling Analyst, Sr. is $98,926.
5. What are the responsibilities of Data Modeling Analyst, Sr.?
Data Modeling Analyst, Sr. develops data models to meet the needs of the organization's information systems. Manages the flow of information between departments through the use of relational databases. Being a Data Modeling Analyst, Sr. maintains data integrity by working to eliminate redundancy. Stays informed of the ways the organization uses its data. Additionally, Data Modeling Analyst, Sr. requires a bachelor's degree. Typically reports to a manager. To be a Data Modeling Analyst, Sr. typically requires 4 to 7 years of related experience. Contributes to moderately complex aspects of a project. Work is generally independent and collaborative in nature.
6. What are the skills of Data Modeling Analyst, Sr.
Specify the abilities and skills that a person needs in order to carry out the specified job duties. Each competency has five to ten behavioral assertions that can be observed, each with a corresponding performance level (from one to five) that is required for a particular job.
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Analysis: Analysis is the process of considering something carefully or using statistical methods in order to understand it or explain it.
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AWS: Amazon Web Services, Inc. is a subsidiary of Amazon that provides on-demand cloud computing platforms and APIs to individuals, companies, and governments, on a metered pay-as-you-go basis.
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Big Data: Big data is a field that treats ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many cases (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy and data source. Big data was originally associated with three key concepts: volume, variety, and velocity. Other concepts later attributed to big data are veracity (i.e., how much noise is in the data) and value. Current usage of the term big data tends to refer to the use of predictive analytics, user behavior analytics, or certain other advanced data analytics methods that extract value from data, and seldom to a particular size of data set. "There is little doubt that the quantities of data now available are indeed large, but that's not the most relevant characteristic of this new data ecosystem." Analysis of data sets can find new correlations to "spot business trends, prevent diseases, combat crime and so on." Scientists, business executives, practitioners of medicine, advertising and governments alike regularly meet difficulties with large data-sets in areas including Internet searches, fintech, urban informatics, and business informatics. Scientists encounter limitations in e-Science work, including meteorology, genomics, connectomics, complex physics simulations, biology and environmental research.