VIDEO: Big Data and The 5 V’s

5. It’s a powerful number isn’t it? The 5 east asian elements. The 5 olympic rings. Or even in the fictional world: the Scooby Gang, the Power Rangers, or the Avatar Gang. No, not the blue ones, these guys. As time marches on and technology advances, we have a new collection of 5 to look towards: The 5 V’s of Big Data: Volume, Velocity, Variety, Veracity, and Value. Before we get into all that though, hi! I’m Kyle. And today, I’ll be chatting with you about those 5 V’s of big data.

And if you want more info on business intelligence tools to help your company navigate big data, check out our website at technologyadvice.com. If you find this video useful, it’d help me a lot if you hit those like and subscribe buttons down below. While big data, the trillions of data points collected across organizations, can be mined for useful info, it's how the data is analyzed and what those organizations do with that insight that's important." There are numerous challenges, namely those 5 V’s I mentioned earlier, that all organizations have to tackle when it comes to working with big data.

Volume refers to the colossal amount of data that inundates organizations. Companies of 15 years ago handled terabytes of data. Today, data has grown to petabytes if not exabytes of bytes (that’s 1,000–1 million TB) that come from sources such as transaction processing systems, emails, social networks, customer databases, website lead captures, monitoring devices and mobile apps. To handle all of this data, managers use data lakes and warehouses or data management systems.

They store it on clouds or use service providers such as Google Cloud. And as global data grows from two zettabytes, (that’s 1 billion terabytes each), at the beginning of the decade to 181 zettabytes a day by 2025, even these may be insufficient. Apache’s Hadoop splits big data into chunks, saving it across clusters of servers. Check out Cloudera Enterprise 4.0 with its high-availability features that makes Java-encoded Hadoop more secure. Big data grows fast.

Consider that, according to Zettasphere, there are around 3,400,000 emails, 4,595 SMS, 740,741 WhatsApp messages, almost 69,000 Google searches, 55,000 Facebook posts, and 5,700 tweets made per minute. More critical still, data ages fast. As Walmart’s former senior statistical analyst Naveen Peddamail said, “If you can’t get insights until you’ve analyzed your sales for a week or a month, then you’ve lost sales within that time.” Competitive companies need some capable business intelligence (BI) tools to make timely decisions.

For instance, Splunk Enterprise monitors operational flows in real time, helping business leaders make timely decisions. That said, it is expensive for large data volumes. Variety refers to the different types of digitized data that inundate organizations and how to process and mine these various types of data for insights. At one time, organizations mostly gained their information from structured data that fit into internal databases like Excel.

Today, you also have unstructured information that evades management and comes in diverse forms such as emails, customer comments, SMS, social media posts, sensor data, audio, images, and video. Companies struggle with digesting, processing, and analyzing this type of data and doing so in real time. For small to midsize companies, Tableau is ideal since it is also designed for non-technical users, and helps to analyze and process all of these various types of data.

Veracity is arguably the most important factor of all the five Vs because it serves as the premise for business success. You can only generate business profit and impact change with thorough and correct information. Data can only help organizations if it’s clean. That’s if it’s accurate, error-free, reliable, consistent, bias-free, and complete. Contaminating factors include: Statistical data that misrepresents the information of a particular market Meaningless information that creeps into and distorts the data Outliers in the dataset that make it deviate from the normal behavior Bugs in software that produce distorted information Software vulnerabilities that could cause bad actors to hack into and hijack data Human agents that make mistakes in reading, processing, or analyzing data, resulting in incorrect information To tackle this, a BI system must be able to handle queries to check the veracity of the data that passes through the system.

Multilingual and scalable Apache Spark is good for quick queries across data sizes. Big data is the new competitive advantage. But, that’s only if you convert your information into VALUE. Users can capture value from that data through: Making their enterprise information transparent for trust Making better management decisions by collecting more accurate and detailed performance information across their business Fine-tuning their products or services to narrowly segmented customers Minimizing risks and unearthing hidden insights and Developing the next generation of products and services Finding value in data can be made easier by thinking out of the box.

For instance, Splunk enterprise helps businesses analyze data from different points of view and has advanced monitoring features that come at a price. That wraps up our video on the 5 V’s of Big Data. Thanks for watching! If you made it to the end, help us out with a like and subscription down below. If you want more info on BI tools that can help your company address these challenges, visit our website at technologyadvice.com for our free list of the best options available today. Click the button on the left to get started.