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The Vs of Data to enhance Big Data Management

The increase in the importance of data has led to it being an industry of its own — that of collecting and managing big data, called Big Data Management (BDM).

According to www.smartdatacollective.com, “Big data is any data sets too large to process using conventional methods like an Excel spreadsheet, PowerPoint or text processors. Sometimes, it takes parallel software running on thousands of servers just to handle big data. Things like keyword research, social media marketing, and trend searches all use big data applications.”.

To manage huge sums of data efficiently, it is important to first identify the various characteristics of data that can help determine what specific data is important to your company, especially in decision making, forecasting, and market expansion.

To make it easier, we’ve broken down the characteristics of data into eight elements. Let’s look at the 8 Vs of data than can help enhance your company’s BDM.

1. Volume – Can you find the information you’re looking for?

Volume refers to the amount of data, which is a vital filtering tool in BDM. Data is continuously generated not only by the company, but also its employees, clientele, partners, and machines. For example, hundreds of millions of smartphones send a variety of information to the network infrastructure.

Hence, more sources of data lead to an influx of data banks, therefore making it pivotal to filter the data being acquired through various software such as Apache Hadoop, Cloudera, and Cassandra.

2. Velocity – How fast are you acquiring data?

Velocity refers to the speed at which data is generated. High-velocity data is generated in speeds that require specific processing techniques. Examples of high-velocity data include Twitter messages, Facebook posts, and e-commerce transactions on online shopping platforms such as Lazada.

The emergence of Industry 4.0 technologies such as the Internet of Things (IoT) has enabled companies to process data in real-time through cloud-based services, making it easier to process the acquired data which can be meaningful information in decision-making processes.

3. Variety – What formats of data is being acquired?

Data is gathered from a variety of sources such as texts, photos, videos, audio, even data acquired from various sensors. The diverse source of data requires distinct processing capabilities and specialist algorithms which can help determine meaningful data formats suited for your company.

For example, an autonomous vehicle (AV) manufacturer will use data captured from the sensors on their vehicles in the picture, audio, and video formats to determine the functionality of the AV in real-life situations and can then, use the acquired data to improve capabilities of the AV in future developments.

4. Veracity – Are you dealing with information or disinformation?

Veracity refers to the quality of the data captured. High veracity data contains information that is meaningful to the company, especially to be used in decision-making processes, forecasting market performance, and determining the target audience for products, which can make or break a company.

The software mentioned above can help filter high and low veracity data, ensuring your company acquires only what is necessary, avoiding the hassle of manually filtering them.

5. Visualization – Can data make sense at first glance?

To communicate information clearly and efficiently, use statistical graphics, pie charts, information graphics, and other tools. This will not only group various data together but also makes it easy on the eyes – instead of seeing numbers and information which are not understandable, data visualisation enables every Tom, Dick, and Harry to understand the captured data.

Visualising data also makes it easier to notice flaws and take immediate action, which is also essential in ensuring business sustainability and clear communications within a company.

6. Value – What is your data worth?

Can the data acquired and analysed, help your company grow? Can it help make informed decisions regarding your company’s future? These are some of the questions you must consider before determining the value of data.

One common technique applied by established companies is the Customer Lifetime Value (CLV). The CLV is predicted through customers’ transaction data and allows decision-makers to undertake the most relevant and profitable business actions, based on the data acquired.

With the data, companies will know which products customers are attracted to, the demands, and other important factors that can attract revenue.

7. Viscosity – Does your data call for action?

Viscosity measures the resistance to flow in the volume of data. Resistance can occur in various data sources, the analytical process, and data filtering. This is a natural cause and is bound to happen due to the vast pool of data that is being generated simultaneously every second.

The aforementioned BDM software is designed to deal with viscosity through various features such as real-time data streaming, complex event processing, and cloud services, allowing decision-makers to constantly work on improving the foreseeability of the company.

8. Virality – Is your data spreadable?

Virality describes how quickly information gets disseminated across people-to-people (P2P) through various channels such as social media networks, mobile applications such as WhatsApp and even broadcast media.

This factor can determine how much buzz your company is creating amongst a network of people, which can be used to determine the success and failure of your company. Virality is important because it does not only determine the success of a product, but it also helps determine the failures of a product.

BDM comprises an integration of technologies and processes to enable broader data gathering, analytics, and usability. A BDM strategy must consider the 8 Vs mentioned above to ensure they provide the context required to move from real-time to “right time”.

This can be done using tools embedded in BDM software such as metadata management, data standardization and cleansing, and stream processing engines. Proper utilisation of these tools, while considering the 8 Vs of data can dramatically enhance your company’s BDM.

*Contents sourced from: www.zarantech.com, www.smartdatacollective.com, www.sas.com, www.bigdataframework.org, www.datasciencecentral.com

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