In today’s digital economy, data is generated from multiple sources at almost unimaginable rates. For companies, it means having access to a vast amount of data to develop effective business strategies. Whether the goal is to reduce costs, manage risks, enhance the efficiency of operations or improve profitability, the advantage of data analytics is that it helps companies to achieve their goals by backing their decisions with accurate data, thereby improving the chances of their strategies succeeding in a highly competitive marketplace.
The main challenge of using big data lies in making sense of it, as every day, more and more data is gathered and stored from varied sources such as emails, social media posts, photographs and videos. Additionally, there’s the risk of fake data providing inaccurate results that negatively impact decisions. As a result, it can be overwhelming to sift through the vast volume of data for business decision making. This is where, the 5Vs of data – Velocity, Volume, Value, Variety and Veracity – can help in determining which data is relevant for providing insights that help the company devise effective strategies to gain competitive advantage.
Velocity: As one can guess, it refers to the speed at which enormous amounts of data are collected, analysed and transmitted in real time. Artificial Intelligence tools make the process simpler by analysing data as it is being generated, thereby eliminating the need for organising it into databases.
Volume: A large amount of data being generated every second from multiple sources such as social networks, mobile phones, credit cards, makes it impossible to store it at a single location. Instead, distributed systems are employed, wherein data storage takes place in different locations, and software is used to bring together or retrieve the data for analysis.
Value: While data is essential for providing accurate insights, it’s pointless to have access to large amounts of it unless it can be processed to add value to the decision-making process. For businesses, this necessitates weighing the costs and benefits of collecting and processing different types of data to ensure that it generates value that can be monetised.
Variety: Unlike in the past, when data was structured into specific criteria that could be neatly organised into a table or a database, the data available today is unstructured as it is gathered from multiple sources in a variety of formats, including photographs and videos. Therefore, the processing and analysing of data is also quite different from that of the past and is dependent on artificial intelligence tools that allow it to be collected, stored and analysed simultaneously.
Veracity: Last, and perhaps the most significant is the veracity or validity of the data. It’s no use collecting huge volumes of data if it doesn’t provide reliable insights to support decision making. For instance, posts by fake users on Facebook or Twitter providing unreliable data that leads to inaccurate insights that can prove detrimental to business decision making.
Each of the 5Vs of big data plays a role in the process of providing insights. Undeniably, veracity is the most significant factor among them. It’s essential that data should be clean so that it offers reliable business intelligenceto support data-backed decisions. Similarly, inaccurate or untrustworthy data can negatively impact the effectiveness of strategies. While the process of collecting and storing data is made easy by artificial intelligence, it’s essential to ensure the accuracy of data for providing reliable insights. Moreover, when data is processed for predictive analysis, improper filters can result in inaccurate target audiences or customer segments.
Ensuring clean data is crucial. While there is no shortage of data that companies can use to gather insights, the validity of the data can contribute towards the success of marketing campaigns or business goals, and here the source of data becomes significant.For instance, Coca Cola collects its data directly from its consumers based on information provided by them when they enrol for the brand’s loyalty program. After analysing the data, the company works our strategies for increasing consumption of existing lines and upselling new products. The use of valid data has not only resulted in sales growth but also reduced costs and increased revenue by helping the company alter its organisational structure.
McDonald’s recent purchase of Artificial Intelligence company Dynamic Yield is aimed at giving the company real-time access to information on consumer tastes, which can then be linked to the kitchen to reduce waste. In a market, where consumers are moving away from junk food to healthier options, the company plans on using the information on what the customer purchases, to perform predictive analysis to understand what the customer needs so that they can offer a more personal and customised experience.
As it can be seen, clean and trusted data can influence the success of the business strategy, just as inaccurate data can hurt a company’s reputation. Clearly, in the future, big data will continue to play a significant role in business decision making. Therefore, investing in tools that support data-backed decisions can dictate the success or failure of campaigns and help a brand gain competitive advantage.
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