Big Data Testing – Big Data QA

Big data has big value, but it’s often a challenge for companies to find the link between the sheer volume of data they handle and the actionable insight they want. Consider this: While experts peg the big data market at more than $130 billion per year, recent research suggests that “bad data” is costing companies $3.1 trillion annually.

If that number seems high, it is. But here’s the hard truth: It’s not unreasonable. Dealing with data that doesn’t make sense, isn’t properly formatted and contains point-of-collection errors costs time and money — managers, data scientists, frontline staff and third-party collaborators have to account for, adjust, and correct this data (if possible). Every. Single. Day.

This is why you need better big data testing. A better way to profile, prepare and validate your data so you’re able to actively — and reliably — leverage this resource.

XBOSoft can help.

The 100 Percent Problem

Anything less than 100 percent isn’t good enough when it comes to data accuracy and validity. Why? Because you’re depending on this resource to inform both current initiatives and deliver ongoing big data business intelligence.

So, what’s wrong with your big data? Why isn’t it living up to expectations? Common causes of “bad data” include:

  • Variable sourcing. Your data comes from everywhere. Emails, text messages, images, e-commerce transactions, social media sites and spreadsheets. The challenge? Format varies and most of this data is unstructured. If you can’t bridge the gap between data types and sources, you’re not getting the full value of the data you have.
  • Source data errors. For big data to have value, it must be error-free. But what happens when errors occur at the source? You need a way to detect — and correct for — source data errors as they emerge.
  • Unexpected results. What happens when your data contains unexpected content such as bad email addresses, unpaired JSON data or format inconsistencies. Left unchecked, these results could prompt everything from unnecessary data studies to strange modeling behaviors and even bad business decisions.

How do you avoid the big data pitfall, deliver actionable big data BI and pave the way for artificial intelligence (AI)? Our three-pillar QA and testing process has you covered.

Pillar 1: Data Profiling

To leverage big data resources, you need to know more about data itself. Where did it come from? What characteristics does it display? How does it relate to other data? Our data profiling tools collect critical characteristics about your source data using value distribution graphs or summary statistics for every data column. Output comes in the format of your choice: HDFS, Cassandra or cloud-compatible and ready for loading into your existing data infrastructure.

Pillar 2: Data Preparation

Not all data is created equal. As noted above, missing, empty or redundant data fields cause aggregation issues and can increase the total cost of big data initiatives as IT teams and managers are forced to identify and then remedy missing or incomplete datasets.

XBOSoft’s data preparation combines both your business requirements and feedback gained during data profiling to deliver specific column aggregation, new column creation and/or transformation as needed — giving you the clean, complete data required to derive statistical results, perform drill-down analysis and begin layering on big data AI solutions.

Pillar 3: Data Validation

Want better data? Implement effective big data QA. Our data validation services identify data value limit ranges and deliver automated notifications to ensure you’re never in the dark about the quality and consistency of your data.

By combining source, process and output validation, we’re able to deliver superior QA that empowers big data BI while avoiding delays, limiting confusion and reducing the time between data collection and actionable insight.

The XBOSoft Advantage

Testing is what we do. It’s how we’re built. It’s our mission to save you time and money. When it comes to big data, our testing and QA services are designed to take your BI, analysis and AI initiatives to the next level.

Why us? Because everything we do is built on our Service-as-a-Partnership (SaaP) model. You’re assigned an expert lead QA Engineer dedicated to understanding and meeting your business needs, backed by XBOSoft’s decade of experience and end-to-end big data testing services.

Ready to get the most from your data?

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