5 Tools To Make Data Analysis Simpler

Posted: Jun 15 2018, 12:30pm CDT | by


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5 Tools to Make Data Analysis Simpler

5 Tools That Help with Data Analysis

Big data practices have compiled mounds of useful information, particularly for businesses who are striving to stay competitive. But trying to deal with massive amounts of data takes time, energy, and knowledge that’s not always readily accessible.

Fortunately, there are tools you can use to stay on top of it.

1. Dashboards

Converting your data sets into visuals can turn complex numbers into useful information that almost anyone can grasp. Dashboarding tools empower you to create graphical contexts for your raw data.

This can help tell a credible story, which makes all the information you can amass as useful as it can be. Dashboarding tools come in a variety of options, including interactive visuals and plug-and-play dashboards (think calculators, charts you can manipulate, etc.).

Dashboards are most useful when you’re trying to explain complex data sequences in a way that will have an impact. They can turn the most complex jumble of numbers into a fully comprehensible story.

They’re also great for presentations when you need to make a strong impact on viewers and leave them with a positive impression. Dashboard products can highlight the most vital metrics and explain their significance.

You should invest in a solid dashboard designer to get the most of your data. It will improve your presentations and make it easier for people to understand the data you’re presenting to them.

2. Analytics Tools

Data analysis is virtually impossible without a strong analytics tool. Such tools offer a variety of benefits to your data processing, including:

  • Single-Domain Decisions: Data analytics tools are designed to accomplish a single purpose, whether it might be to showcase your website followers or build your email list. An analytics tool will gather the data you need to accomplish the task.
  • Data Collection: Most analytics tools handle data collection before analyzing it. That’s one extra step you may cross off your list.
  • Answering Common Questions: You probably have a list of questions you want to answer, such as “What’s my website bounce rate?” or “Which blog posts perform best?” Analytics tools will settle these questions for you.

There are many analytic tools for businesses, whether they’re built into another tool, or function as stand-alones. The most common is Google Analytics, which is free and fairly easy to use.

3. Spreadsheets

The most common spreadsheet tool is the long-term standby, Microsoft Excel, and spreadsheets remain one of the best data tools on the market. They’re easy to learn and efficient for configuring certain data and calibrating it.

Spreadsheets are particularly useful for financial modeling, one-time analysis, and brainstorming. You can easily reframe spreadsheets to source data, analyze it, draw conclusions, and even make visual presentations.

Unfortunately, it’s also pretty easy to make mistakes in spreadsheets, because those are primarily caused by humans. Such errors can often be difficult to locate, as well.

According to one study, about 88 percent of all spreadsheets contain errors, so be aware of this when you use them.

4. Structured Language Query (SQL)

A universal language that’s associated with data collection and analysis is called Structured Language Query (SQL). You may access this useful language through an SQL client who can interpret the language and ask questions in that language.

It’s particularly useful for one-time analyses. If you have a question you need to be answered quickly and thoroughly, an SQL query offers a swift and easy method for achieving that goal. It’s perfect for specific-number questions, such as “How many people ordered product yesterday?”

SQL queries can be difficult to maintain, though. Especially as your questions become more complex. It’s most effective when used in combination with other data analysis tools.

5. Statistical Software

Many of the software aids we’ve discussed have evolved from simpler data collection and analyzation processes. As your needs grow more complex, so will the software you will prefer, even have, to use.

Statistical software can handle more rigorous analytic needs, such as analyzing the overall effectiveness of a campaign. One of the primary strengths of statistical software is its ability to answer non-numerical questions, like: “What are the shopping behaviors of my target audience?”

It’s also useful for advanced market segmentation, to help you target your audience and decide between competing options. It can form hypotheses and then collect data so you can identify which option to accept and which to reject.

This is not an easy tool to master, so you may need to outsource the use of statistical software to a data analytics company. Still, it’s a worthwhile consideration as you evaluate your data processes for the purpose of maximizing your firm’s earning potential.

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The Author

<a href="/latest_stories/all/all/68" rel="author">Larry Alton</a>
Larry is an independent business consultant specializing in tech, social media trends, business, and entrepreneurship. Follow him on Twitter and LinkedIn.




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