What is Big Data?
In data analytics, it is very important to study patterns in between the data and forecast upcoming phenomena for better performance. Data science is not just analyzing data and vast amounts of information but is also about digging through such patterns of information in order to find insightful information for future use.
Unlike traditional times when humans had to analyze through data, contemporary data analytics relies on computers and machines to conduct such analysis through data. However, the case is different when it comes to big data.
Hard-to-control data, referred to as Big Data, is humongous and difficult to manage. When it comes to data analytics of Big Data, the process of digging into data is faster, bigger, and diverse.
Moreover, the artificial intelligence algorithms required to conduct analysis for Big Data are more complex and structured to handle vast amounts of data.
"In layman’s terms, Big data describes a large volume of structured and unstructured data that engulfs a business on a daily basis. It is primarily defined as the three Vs - volume, velocity, and variety. "
Defining Big Data
Benefits of Big Data
Broadly, the use of Big Data technology components has many benefits that can facilitate the profit-making potential of businesses and accelerate the efficiency of work management. Here is a brief list of Big Data benefits to help you understand the concept well.
Better Decision-making Instincts
Big Data Applications can have a lot of benefits when it comes to businesses and organizations. However, one of the biggest advantages of Big Data is that it helps in better decision-making instincts.
Since it is capable of digging deep into the information and developing patterns that provide insights, Big Data can be very helpful in helping your organization make more informed decisions based on the extracted data from past records.
Henceforth, data analysis in the retail industry can lead to better decision-making power among retail businesses.
As soon as insightful extracts are collected from Big Data, algorithms can help organizations achieve efficient and detailed predictive analytics techniques.
Simply put, Big Data enables computerized algorithms to accumulate insights from larger datasets to arrive at accurate conclusions and better results.
This way, the obtained predictions are way more reliable and beneficial in the long run.
When combined with predictive analysis, Big Data builds a strong foundation for data extracts that can be worked upon strategically and lead to higher profits in the business realm.
Ensures Data Privacy
Another benefit that Big Data offers is that it ensures data privacy. Since the data that is handled under this concept is way more complex and structured, several formats are employed to manage Big Data that protects sensitive data and classifies the rest accordingly.
Without hampering or revealing any data insights, Big Data Analytics tools only work on the lines of the required insights and do not walk away from the focus. Therefore, it surely ensures data privacy and security.
Big Data in Retail Sector
Even though you might have understood that Big Data is very helpful in our everyday lives, you will now be reading about Big Data in the retail sector.
When it comes to the use of Big Data in the retail sector, a lot of Big Data applications can be included in this discussion. Let us discover the applications of Big Data in the Retail sector 2020.
One of the most prominent uses of Big Data in the retail sector is that such a vast amount of data can very well provide accurate results for customer preferences.
Thanks to technological advancements, Big data analysis techniques can help machine learning algorithms to dig into data and conjecture customer preferences based on an individual's past purchase records and buying history.
In the retail sector, understanding the psyche of a customer and analyzing the kind of products s/he desires is extremely helpful to promote the target products and help companies make profits in considerable time.
With Big Data, this can be achieved in the contemporary marketing scenario where technology has opened many windows for retail professionals to understand what their customers actually want.
Even though data mining scientists suggest that a handful of datasets cannot accurately suggest what kind of customer preferences are the most desired, there is some other revelation that they have to make.
On the other hand, as they suggest, Big data science tools can accurately indicate customer preferences by employing trained algorithms with as many samples as possible.
Optimization of Product Portfolios
While customer preferences are one aspect of the retail sector, product reports are another such aspect that holds a very eminent position in this field. In light of this, Big Data can also be applied in the optimization of product portfolios.
As customer feedback reports are accumulated through the source of Big Data, sales departments of various companies can optimize their product images and overall portfolios.
This helps them to understand what additions they can put in their products and what features are unwanted by customers.
Not only is this helpful for both customers and companies but it also makes the two-way flow of commodities much more efficient and enhanced.
The collection of customer feedback reports also helps to evaluate a company's performance in the long run and offers remotely available reviews for the progress of a brand.
"Aldo is a shoe and accessory company based in Canada that uses big data to address this crazy time of year. The company operates on a service-oriented big data architecture, integrating multiple data sources involved in payment, billing, and fraud detection. This integration project enables Aldo to deliver a seamless ecommerce experience—even on Black Friday."
Big Data Uses in Retail Industry
Supply Chain Management
Another very important application of Big Data analytics can be observed in the field of the supply chain. In the retail sector, the supply of products is an extremely crucial role as it brings the products from one point to the other.
In such a case, many loopholes can occur in between the supply chain while products are being sent from one end to the other. Perhaps this is where Big Data enters into the scene and plays its role.
In every supply chain management system, Big Data can forecast any inefficiencies and can also detect anomalies, in case there are any.
With the ability to detect anomalies, Big Data can break down obstructions in supply chain management and can readily serve as a self-healing chain that lets the retail sector rectify such errors.
For instance, a chocolate manufacturing company supplies a fixed number (for instance, 100) of products to a grocery store in your locality.
However, due to some glitch, the process only supplies 25 pieces in the month of March. Yet, Big Data can run through such data and detect any such anomalies that will instantly let the company know about any loophole.
Detecting Quality Deficits
Besides detecting anomalies in the supply chain management, Big Data can also help the retail sector to identify quality defects in the products manufactured by a company.
Retail chains use Big Data analytics to dig into data for quality deficits and evaluate a product's performance in the market. That said, Big Data in the retail sector can be of great use to data scientists who employ several procedures and mechanisms powered by AI. (Learn more about how big data analytics uses AI)
In order to boost quality improvement in retail businesses, data scientists look for the best procedures to conduct retail operations and find the perfect match for their quality standards in order to compete with other such dealers and provide the best they can.
"Once we have derived intelligence from this data, we will be able to apply universal best practices across all plants to better align processes and improve quality performance."
Big Data in Retail Sector
Predictive Analysis of Sales
Even though you might have been awestruck by the applications of Big Data Analytics in the retail sector, there is one more use that can fully amaze you.
With the help of predictive analytics tools, Big data scientists can conduct predictive analysis of sales that forecasts product demands in various demographic areas and among various target groups.
One of the biggest things that Big Data provides us with is vast amounts of data records obtained from the past and present. Thus, these records can be used to identify what seasons or what time periods witness more sales of a particular product.
In turn, this identification helps companies in the retail sector to prepare accordingly and deploy their sales teams during such times in the year. Apart from being an application, this use of Big Data also serves as the biggest benefit of this technology in the retail sector.
Future of Retail Sector and Big Data
The future of Big Data tools in the retail industry is all about expanding opportunities and increasing the profit-making capacity of businesses at large.
Even though most of the retail operations are managed with the help of Big Data companies, the coming years could witness greater technological aspects being collaborated with the sector.
When it comes to the future applications of Big Data in the retail sector, one can expect data scientists to progress substantially. One of the best examples of the future of the retail sector can be understood in light of retail robots.
Not only these retail robots will make data collection more extensive but will also the inefficiency and accuracy of purchasing patterns