How Data Velocity is the game changer for beverage industry.

Velocity is the rate at which data is processed, and it covers inputs such as how social media is processed, as well as outputs such as processing and to process and execute. The levels of data velocity are as follows:

• Real Time: Data is processed in the amount of time that is required, implying that you are processing data that is sufficient to handle data or events as they occur. This entire process is extremely straightforward and quick, for example, a person makes an application for a debit card and receives a response almost instantly.
• Near Real Time: The data is processed as soon as the event is occurred but not as fast to respond it quickly. For example, you applied for debit card, and they evaluate, process and then the application go ahead and get an answer within hour.
• Batch: The data processing is done when computing resources and are available the process goes behind and catches up. For example, a social media platform that runs algorithms to look privacy violations.
• Custom Job: This processing involves data batch vies, which is unique and might be executed once or comes with an irregular schedule.
• Analytical Processing: This process is tied to decision making and to oppose business events. This can be done in both real time or near real time such as decision making and can also explore data.

How can big data velocity work for Beverage Industry?

                                                     “No great marketing decisions

                                                                   have ever been made

                                                                     on velocity data.”

                                                                                 – John Sculley

 

Because big data is produced in such large numbers, you'll need more than just space to adequately process it—you'll also need speed. It's no longer about how much data you collect; it's about how quickly you can use it to make business decisions.

An organization like beverage firms had to wait for data to be evaluated and interpreted in the past. However, with the constant inflow of data, it must now be analysed and digested swiftly. You'll wind up with a tremendous backlog of information if you don't work quickly enough; given how quickly the business world moves, that hard-earned information may be obsolete by the time you acquire it.

Data is believed to age like wine, which means the longer you keep it, the more insights you'll get out of it. While this analogy may hold true for some types of data, it may not apply to other cases. Many types of data have a finite shelf life, meaning their value can deteriorate with time—and in some circumstances, fast. In retail, for example, knowing which products are out-of-stock in seconds or minutes rather than days or weeks is preferable. The faster can beverage a retailer can refill its products, the faster it can get back to selling them.

Using real-time alert some beverage companies was popular in most of its stores—except two locations where it wasn’t selling at all. A quick investigation at those two locations revealed a simple stocking oversight meant the drinks weren’t yet on the store shelves. If that beverage store discovered this stocking problem after the fall, the value of this insight would have already vanished. Data velocity doesn’t just apply to the retail industry—it can apply to many diverse business models and functions.

Following are the terms in which the beverage business can use this data velocity process by using Data Processing Cycle.

 What is Data Processing Cycle?

(What Is Data Processing: Types, Methods, Steps of Data Processing Cycle, 2021)

Step 1: Gathering:

The initial phase in the data processing cycle is the acquisition of raw data. The raw data obtained has a significant impact on the product produced. As a result, raw data should be acquired from defined and accurate sources in order for the resulting conclusions to be valid and useable. Raw data can contain monetary information, website cookies, a company's profit/loss accounts, user behavior, and so on.

Step 2: Get Ready

The act of sorting and filtering raw data to remove unneeded and erroneous data is known as data preparation or data cleaning. Raw data is reviewed for errors, duplication, miscalculations, and missing data before being translated into a format appropriate for further analysis and processing. This is done to ensure that only high-quality input enters the processing unit.

Step 3: Enter your data

The raw data is transformed into machine-readable form and sent into the processing unit in this step. This can take the form of data entry via a keyboard, scanner, or other input device.

4th Step: Data Processing

In this step, the raw data is exposed to a variety of data processing technologies, including machine learning and artificial intelligence algorithms, in order to produce a suitable output. This stage may differ differently from process to process based on the data source (data lakes, online databases, linked devices, etc.) and the intended use of the result.

Step 5: Results

Finally, the data is transferred and shown to the user in a readable format, such as graphs, tables, vector files, audio, video, documents, and so on. This output can be saved and processed further in the next data processing cycle.

Step 6: 

Storage is the final phase in the data processing cycle, where data and metadata are saved for later use. This enables for easy access and retrieval of information when needed, as well as immediate use as input in the next data processing cycle.

Conclusion:

Data Velocity has been game changer in beverage industry as the method of collecting data and processing them is quite structure which makes it easier to understand and evaluate further.

 

 Author - Ritika Tiwari

[4th July, 2021]

Focus Keyword: #beverage #datavelocity #dataprocessing #datatypes #bevergeindustry #digitalmarketing

 

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References:

Spacey, J., 2021. 5 Types of Data Velocity. [online] Simplicable. Available at: <https://simplicable.com/new/data-velocity> [Accessed 4 July 2021].

Simplilearn.com. 2021. What Is Data Processing: Types, Methods, Steps of Data Processing Cycle. [online] Available at: <https://www.simplilearn.com/what-is-data-processing-article> [Accessed 4 July 2021].

Youtube.com. 2021. Before you continue to YouTube. [online] Available at: <https://www.youtube.com/watch?v=oxUbbWRAqxg> [Accessed 4 July 2021].