What does a data analyst do?

As a data analyst, someone typically handles data coming from or going into a data warehouse or business intelligence system. They compile the reports, verify the quality (integrity), and use the data to assist executive- and senior-level staff to make informed company decisions. The work can also include information visualization, statistics, and/or database application design, depending on the needs of the organization.

Examples of data warehouses (possibly) include Salesforce, SQL Server 2008, Oracle 11i, and mySQL. These relational database management systems (RDMS) are custom-built specifically for organizations. The logic and programming for even a small database requires expert knowledge, and large ones can require many months and extensive planning. Data analysts often have some formal background in database logic, relational algebra/calculus, and programming, and assist the database developer in constructing a solid schema for the relational database.

When it comes to data, a huge part of the data analyst’s job includes programming in the computer language known as Structured Query Language (SQL). Each database system has its own varient or flavor of SQL, but there are basic rules with SQL that apply across the board. Many newer technologies include Hadoop, data warehousing, and Big Data analysis, which are at the cutting-edge of the data-science world in 2011.

There are some evolutionary changes in data science – for instance, data mining has become a standard strategy for uncovering patterns. Data mining is heavily reliant on algorithms and statistical methods, which are used by applications such as RapidMiner, Weka, and/or R (the mathematics program), in order to discover knowledge.

In order to be a data analyst, it is almost always mandatory to have at least some college background. It is a rigorous field, much as any computer science-based occupation. Solid knowledge of current data techniques is vital, and being willing to continually upgrade and train for new skills and developments is also imperative. Having a background in mathemathics, computer science/information systems, statistics, finance, or economics will be a benefit; graduate school is also an option, and can assist with advancement.

Related articles

• Too many cooks spoil the data warehouse broth (go.theregister.com)
• Tech job-seekers: Hadoop skills are in high demand (infoworld.com)
• Big Data Analytics: Trends to Watch For in 2012 (allthingsd.com)