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Data Analyst

What is a Data Analyst?

Skills That Set Them Apart

Data Analysts organize information into quantifiable content, so their skills need to be heavy on math and statistics. They also need to be:

01

Skilled collaborators

The most successful Data Analysts foster relationships from every department in order to understand what the data needs to measure. It may not be enough to know when customers are buying – an easy enough query – but the real reveal may be why customers buy at that particular time. Analysts can help you discover the less obvious insights when they know which questions to answer.

02

Solid communicators

If you can’t explain it simply, you don’t understand it well enough. Data Analysts have to know what the data shows mathematically, but more importantly, they must be able to apply it to the real-world scenarios. They have to be able to demonstrate how the data answers the query and then discuss what it all means in layperson’s terms.

03

Bottom-line experts

Many times, stand-alone data means very little until it’s compared with other information. For example, a year-end report can stand on its own, providing important feedback for bottom-line results, but it cannot tell you how your company’s progressed over the past five years, nor can it help you predict what may be in store for the years ahead.

The Educational Foundation That Sets the Stage

Specialized Training

Here are some of the top technical skills that Data Analysts rely on:

01

Alteryx

Data acquisition, application and enrichment are part of the daily life of a Data Analyst. In order to create predictive, statistical and spatial analytics with repeatable results using the same intuitive user interface, they need Alteryx.

02

KNIME

Being able to automate some of the more tedious processes are key for Data Analysts, and KNIME is a great tool that assists in predictive analytics. Its primary function is to integrate various components for machine learning and data mining through a modular data pipelining concept

While the graphical user interface allows for an easier assembly of nodes for data preprocessing, modeling and data analysis and visualization.

03

Python

Python, Java, Perl and C/C++. are all languages that can serve a Data Analyst well. Using to analyze data creates a series of steps, including programming, transforming, discovering and modeling, which can communicate the results in ways that are more preferable and useful to the query set.

Python is more popular than R, although both of these open-source languages are equally viable. In addition, SAS remains in use and continues to see strong support overall within the various Data Management fields.

04

SQL

SQL (structured query language) is the foundation of complex queries because most big data systems use it, along with additional proprietary extensions for more customized use.

Even so, the standard SQL commands such as "Select," "Insert," "Update," "Delete," "Create" and "Drop" can still be used to accomplish most tasks – a universal language to master.

05

NoSQL

Big data calls for big scaling capabilities, and so Data Analysts should be familiar with NoSQL such as MongoDB or HBase.

These systems work quickly with large volumes of data and can scale accordingly for a more customized approach.

06

Big Data Computation Networks

Apache Hadoop, Hive or Pig are great additions to a Data Analyst’s capabilities. Here’s why: Hadoop is built on clusters of commodity computers, providing an easy way for storing and processing data without format requirements.

The bigger the data, the slower the process, so speed is key. Apache Spark is also popular because it’s faster than Hadoop – a boon when running extremely complex algorithms. Familiarity with cloud-based tools can also be a great assistance to Data Analysts. Amazon S3 is one of the more popular ones.

Data Visualization Tools

Being able to communicate their findings is one of the job requirements of Data Analysts, and in order to do so, they need to be familiar with the wide assortment of tools that are at their disposal.

Tableau

Tableau is an essential software package that can present the data and showcase the derived insights. It provides a wide array of tools that allow Data Analysts to drill down further and see the results in a variety of visual formats.

ggplot2

ggplot2 allows Data Analysts to plot trends on a graph with unique color-coding to help distinguish between key points. The findings can then be processed directly as a PDF or object that can be easily disseminated to shareholders.

FusionCharts

FusionCharts is a JavaScript-based formatting software that charts both web and mobile platform data into three-dimensional graphs. According to New Gen Apps, more than 80% of Fortune 500 companies use it.

Non-traditional Data Corralled with Fuzzy Logic

The Average Data Analyst Salary

How much does a Data Analyst make per year? Like most fields, it depends on your experience, location and skillset. Some of the leading job-search companies published their findings:

What to Expect from a Wyzoo Data Analyst

Wyzoo Data Analysts review data for suitability for selected use case. They sometimes recommend to clients how to capture and aggregate data that doesn't exist in order to have data that is useful for analytics purposes. They develop systems for collecting data and then compile their findings into meaningful reports that can provide additional insight into existing conditions and help predict future trends.

They’re your team of experts who are responsible for:

  • Collecting huge amounts of data
    from 1st-, 2nd- and 3rd-party sources
  • Analyzing data to identify patterns
    and create narratives to support them
  • Producing internal
    and external reports to help identify key findings
  • Collaborating with team members
    to help communicate important results
  • Creating visualizations of the data through charts and graphs

Wyzoo’s Data Analysts gather data from a variety of sources to identify market patterns and trends, and then discover how that information can be leveraged to answer questions and solve problems.

When your business can see the big picture and apply those learnings to understand future developments, you’ll be more equipped to meet and exceed your future projections.