Data Analyst


Data analyst



A data analyst is the person of very skilled, which specializes in collecting, organizing, analyzing, and presenting data from various information resources. For example, information may be obtained from a secondary source documents such as statistical studies, or from the direct marketing and consumer surveys. In terms of analysis, data management and reporting systems analyst generally uses data drawn from relational data to collect and organize the specific post. While this process is largely automated, first be initiated by developing mathematical computations and collection protocols, in order to extract and extrapolate the data into meaningful statistical analysis or "what if" scenarios. 
Although the primary tasks of this position are the compilation and analysis of numerical information, a data analyst often takes on other roles. One thing, he or she is expected to possess a certain level of technical expertise with automatic data collection and reporting systems, including the capacity for program and system security measures yeast. Analyzed the nature of the data collected, the individual must be familiar with the signs of the special procedures of the investigation of a part of labor and sorrow.

 In addition, data analysts often connect in making projections about future trends based on current economic and / or market conditions. In some cases, data analyst is engaged in the research phase of the project by participating in the design and implementation of relevant studies and surveys.

SPSS Versions



  • SPSS 15.0.1 – November 2006
  • SPSS 16.0.2 – April 2008
  • SPSS Statistics 17.0.1 – December 2008
  • PASW Statistics 17.0.3 – September 2009
  • PASW Statistics 18.0 – August 2009
  • PASW Statistics 18.0.1 – December 2009
  • PASW Statistics 18.0.2 – April 2010
  • PASW Statistics 18.0.3 – September 2010
  • IBM SPSS Statistics 19.0 – August 2010
  • IBM SPSS Statistics 20.0 – August 2011

Data Analyst Role



Work for Data Analyst
1. Performs logical data modeling
2. Identifies patterns in data
3.  Designs and creates reports
Definition of Data Analyst
‘The Data Analyst is the professional whose focal point of analysis and problem solving relates to data, types of data, and relationships among data elements within a business system or IT system or any other systems.’

The data analyst role can commonly involve the following: 
1)   Collecting the data, documenting the types and structure of the business data that is also known as logical modeling
2)   Analyzing and drawing out data to identify patterns and correlations among the various data points, 
3)   Mapping and tracing data from system to system in order to solve a given business or system problem, 
4)   Design and create data reports and reporting tools to help business executives in their decision making, 
5)   execute statistical analysis of any kind of data.
Other common titles for this role are: Data Modeler, Business Intelligence Analyst, Data Warehouse Analyst, Systems Analyst, and Business Analyst (generic term), etc.  

Statistics is Science



Definition of statistics by BRITANNICA is-
Statistics is the science of collecting, analyzing, presenting, and interpreting data. Governmental needs for census data as well as information about a variety of economic activities provided much of the early impetus for the field of statistics. Currently the need to turn the large amounts of data available in many applied fields into useful information has stimulated both theoretical and practical developments in statistics.

Statistics is a very complex and challenging field. Most scientists we know have a moderately sophisticated understanding of statistics, many know far more of statistics than we, although some apparently less. However, most large studies consult with statisticians who are experts in statistical analysis.

I believe that statistics can be a science in the same sense as physics. The fact that it is split into two branches, frequency and Bayesian, is unsettling. There is no consensus among statisticians on some fundamental issues. This means that users of statistics must apply their own judgment - they cannot fully rely on results of research performed by statisticians in the same way that they can do it in an idealized science that I described above. Statistics does not generate intellectual material of the same kind as in historical research or art so it should try to evolve in the direction of natural sciences such as physics, in terms of consensus.

Statistical analysis is just another tool of modern science – it is part of the technology of science. And like all things, there is a wide variation in quality and understand across individuals, and what filters down to the public is generally oversimplified to the point of being wrong.

Statistics is a very complex area of science and mathematics and much of the problem is that many scientists themselves don’t understand statistics well enough, because of how they view it. Statistics is sometimes viewed as an obstacle to get to the science, but in reality its part of it.

Some people say that,
The problem is that new software packages have made it easy to apply statistical tests even in situations where understanding them is difficult, or they might not be needed at all. Many people have this notion that. Because it is so easy, many people just tack this sort of thing onto the end of papers.
The thing to keep in mind is that each statistical test looks for different aspects of the data and you have to understand what they do in order to determine if the test is appropriate and if the results will be meaningful.

So we can easily  say statistcs is a science.

Pie Charts


Pie Charts
·         A circle is divided proportionately and shows what percentage of the whole falls into each category
·         These charts are simple to understand.

They convey information regarding the relative size of groups more readily than does a table.
chart
pie chart