Veracity for Restaurant Marketing - Cleansing and Transformation

Hello there!

Welcome back to this blog that is made to update you on digital marketing for restaurant trends and, above all, give you the necessary tips to develop growth in reservations within your restaurant and satisfy your customers’ demands.

Today, the topic of the veracity of big data is our article’s protagonist.

Veracity in the system’s data or payment transactions as customer service in restaurants is the key to generating trust and loyalty with your client.

I want to start with a few examples of veracity from data in information concerning before articles:

An SEO report with transparency of information will help us be clear about the objectives and all the company’s results.

Data visualisation is a clear example of a computerised system that offers a broad panorama in which we reflect the information in detail into the graphs.

Fintech and its transparency in handling payment transactions help to visualise the tracking on banking applications, making customers feel secure in any pay.

On the other hand, veracity is also necessary for Business Intelligence to manage data collection and other tools. The accurate and reliable analysis to generate an essential change within any business. Let’s get started!

Veracity is the key to trust.

I will talk about the veracity, cleansing and transparency of Big data.

Big data grow over volume, variety, and velocity alone. Therefore, you need to know big data’s 10 characteristics and properties to formulate for the challenges and returns of big data initiatives. Unfortunately, veracity is one of the unfortunate characteristics of big data. As all the above characteristics increase, veracity (confidence, trust in data) drops.

The term veracity is defined as one of the 5vs of big data, which indicates trust, quality, and credibility of a company or organisation’s data to gain perfect insights for the ideal decision-making system. (Ved, 2019)

Generally speaking, all applications of cleansing, profiling, transformation, discovering etc., should be in terms of data captured or extracted from the web. Therefore, each website should be treated as a source.

It would help if you used language from that standpoint rather than the traditional data integration slant on enterprise data management and data from conventional sources.

Data processing continues only after the data source has been analysed and installed. Therefore, data purification relies on complete and continuous data profiles to identify quality issues.

In general, data veracity is a degree of accuracy or truthfulness of a set of data. However, in the case of big data, it is not just the quality of data that is essential but also about how trustworthy the source, data type, and data processing are.

Sources: datafloq.com

Data veracity has given rise to two other big V’s of Big Data: validity and volatility:

Validity: Springing from the idea of data accuracy and truthfulness but looking at them from a somewhat different angle, data validity means that the data is correct and accurate for the intended use since valid data is key to making the right decisions.

Volatility: The volatility of data, in its turn, refers to the rate of change and lifetime of the data. To determine whether the data is still relevant, we need to understand how long a specific data type is valid. Such data like social media, where sentiments change quickly, is highly volatile. Less volatile data like weather trends are easier to predict and track. Yet, unfortunately, sometimes, volatility isn’t within our control. (Gaur, 2022)

What is Data Transformation?

Data transformation is the process that changes the format, structure and value of data.

Data may transform data at two stages of data pipelines for data analytics projects. First, the organisation’s on-premises data warehouse typically use ETL (extract, transform, load) procedures, and data transformation is one of the steps in this.

Nowadays, organisations mainly use cloud-based data warehouses, which is more advanced. The data can scale computed, stored, and measured quickly. This process can skip the preload transformation and low data into a data warehouse and then transform at the requested time.

Benefits of data transformation in Restaurant Marketing

• Transformation of data will make it well organised. Also, transformed data may be simple for both humans and computers to use.
•  Properly formatted and validated data helps develop applications from null values, duplicates that unexpectedly happened, incorrect indexing etc.
• Data transformation enables performance between applications, systems and data types.

In this context, if we are also talking about transformation in customer service, it is necessary to know the company have to provide the customer with all the positive and negative information about its products and services to make a well-informed sales process. (Gaur, 2022)

Importance of transformation in client service

Customers demand that companies are transparent, and it is the key to generating a significant transformation into the business in their operations and in the information they provide.

And what is the reason? First, they seek security and confidence to acquire products and services. In this sense, I can tell you that transparency is a “requirement” for companies today.

Here are a few reasons why you should consider transformation in your business:

1.    Need for information: Customers need to be informed to make decisions.

2. Gain consumer trust: Nothing is better than being honest with customers. Transparency creates a bond of loyalty with consumers.

3. Competition: Transparency is an attribute that customers value. And it will give you an advantage over your competitors.

4.   Respond to your customers with honesty: Whether in person, on Facebook, through Yelp, or via any other form of communication, answer questions about your restaurant with honesty and transparency. Although it may seem like a risky activity, customers appreciate it. Transparency also shows confidence in your company when you avoid hiding certain or all aspects of your business. As a result, a relationship is established with both customers and employees. In addition, staff members feel more confident in their duties since management has established trust.

5. Be vulnerable with your customers: Creating an open relationship can evolve from having personal conversations. Setting all business-related discussions aside, allow yourself to open up about what your life is like outside of running a restaurant. (Media, 2021)

In conclusion, I would like to add that every business or organisation uses Big Data and implements the new digital culture as their primary tool for development and successful performance. However, it faces the issue of ensuring high-quality data.

To find the solution to these challenges, companies should look into the veracity of data and adapt data governance practices. It will help the companies achieve high-quality trustful, fast data and motivate them to use the full potential of data and achieve the best from the data.

Author: Fiorella Orellana

Keywords used in this note:

#marketingforrestaurant

#importantoftransformation

#whatisdatatransformation 

#veracityforrestaurantmarketing

#cleansingandtransformation

#KnowledgeManagement

#businessintelligent

References

Gaur, C., 2022. XENONSTACK. [Online]
Available at: https://www.xenonstack.com/blog/veracity-in-big-data
[Accessed 22 February 2022].
Available at: https://www.xenonstack.com/blog/veracity-in-big-data
[Accessed 22 February 2022].

Media, Z., 2021. onedine. [Online]
Available at: https://onedine.com/2021/01/29/5-ways-to-increase-your-restaurants-transparency-with-customers/
[Accessed 22 February 2022].

Thompson, S., 2021. VERACITY. [Online]
Available at: https://www.veracityit.com/solutions-services/data-business-intelligence
[Accessed 22 February 2022].

Torrejon, L., 2020. IDC Content Marketing. [Online]
Available at: https://www.blog-idcspain.com/el-problema-de-la-veracidad-de-los-datos-en-un-mundo-data-driven/
[Accessed 22 February 2022].

Ved, M., 2019. DATAFLOQ. [Online]
Available at: https://datafloq.com/read/data-veracity-new-key-big-data/
[Accessed 22 February 2022].