5 Reasons Hadoop Makes Your Data More Valuable

Data is one of those boring but essential components of a successful, modern business. Business leaders rely on research to make marketing and sales decisions, and data records all of the interactions within the business. Since data has so much potential to guide an organization to success, it is surprising how many companies store data that is completely useless to them. It’s not that the data is inherently worthless, but the organization doesn't have the capacity to handle or analyze the data for the information to have value.

While relational databases have been the staple of the business world for decades, it may be time for businesses to switch to a Hadoop distribution that overcomes the following five deficiencies.

1. Inefficient Queries

Data can lead to valuable insights, but only if it can be analyzed frequently. Some companies need to be able to analyze data daily in order to keep up with their business needs, but many databases are too slow to keep up with that kind of workload. This means that valuable insights are slipping through the cracks as businesses pick and choose which analyses to complete, and making quick decisions on current data coming in is next to impossible.

2. Limited Capacity

Coupled with inefficiency, most data systems are unable to handle the surge of data produced online today. It’s estimated that 90 percent of all data in the world has been created in the past two years alone. With the amount of data being created not slowing down, businesses have to pick and choose which data to keep and choose “representative samples” when running queries to accommodate the system’s limited capacity. This means the entire process is subject to human error and bias, which skews results and diminishes the value of the data for actual business application.

3. Limited Data Types

Unstructured data makes up 80 percent of the world’s total data, but relational databases require all data to be structured before they can store it. Most businesses don’t have the time or resources to convert unstructured social or click stream data into a structured form, meaning they are missing out on 80 percent of the data available to them. With online interaction making up such a huge part of business interaction today from eCommerce to marketing and customer service, not having access to unstructured data makes any picture generated by structured data incomplete at best and completely inaccurate at worst.

4. It’s Not Applied

Collecting and storing gigabytes of data may seem like a big accomplishment, but ultimately, collecting data is completely useless. Unless data is analyzed and provides valuable insights that can be used, all of that data is just eating up space and using up resources. In addition, many insights generated by traditional databases come too late or are based on too small of a data set to be able to put them into action.

5. Lack of Competitive Insights

With more and more organizations turning to big data to resolve the problems with the traditional, relational database, those organizations that don’t take advantage of big data analytics will fall behind and miss out on the new insights big data reveals. Companies that take advantage of big data will have access to new customer insights, such as a profile on which items they pin on Pinterest. Not only is this information unstructured, but it would be much too massive for a relational database to handle.

Overall, the switch to online and mobile interactions have made traditional data and their databases obsolete. A company’s inability to process large amounts of data quickly, including in a multi structured form, will cause it to fall behind their competitors as it is left to incomplete data sets and analyzes.