Saturday, March 26, 2022

Veracity-Cleansing and Transformation in Travel Industry

 

                                                        VERACİTY- CLEANSİG AND TRANSFORMATİON

Difference Between Data Cleansing and Data Transformation

The main difference between data cleansing and data transformation is that the data cleansing is the process of removing the unwanted data from a dataset or database while the data transformation is the process of converting data from one format to another format.

A business organization stores data in different data sources. It is important to make decisions by analyzing the data. Analyzing data from multiple data sources is difficult. Therefore, business organizations use data warehouses. It is a central location that stores consolidated data from multiple databases. Data warehouses help to create reports, analyze data, visualize data and make valuable business decisions. In other words, data warehousing supports the overall business intelligence process. Data cleansing and data transformation are two techniques that are used in data warehousing. Data cleansing refers to eliminating meaningless data from the data set to improve data consistency while data transformation refers to converting data from one structure to another structure to make them easier for processing.

Key Areas Covered

1. What is Data Cleansing

     – Definition, Functionality

2. What is Data Transformation

     – Definition, Functionality

3. What is the Difference Between Data Cleansing and Data Transformation

     – Comparison of Key Differences

 

What is Data Cleansing

A business organization uses various sources to store data. They can have different databases such as Oracle, MySQL, etc. It is difficult to analyze data in different data sources. Data warehousing provides a solution to this issue. It helps to collect, store and manage data from a variety of data sources into a central location called a data warehouse. The data warehouse gets data from transactional systems and various relational databases. Finally, this data is processed and analyzed to get meaningful business insights.

The data should be cleaned and transformed before loading into the warehouse. The extracted data from multiple sources can consist of meaningless data. Dummy values, contradictory data, absence of data are considered as meaningless data. These unnecessary data must be removed from the dataset. Overall, data cleaning will not just provide a clean dataset. It also brings data consistency to different sets of data that have merged from various data sources.

 

 

What is Data Transformation

After cleansing, the data is transformed into a suitable format. Data transformation helps to process the data easily. Data transforming can be simple or complex depending on the required changes on the data. Standardizing data, character set conversion, encoding handling, splitting or merging fields, conversion units of measurements into a standard format, aggregation, consolidation, delete duplicate data are some of the tasks involved in data transformation.

After completing the data transformation, the data is loaded into the data warehouse for processing. Finally, the senior management and data analysts can take decisions based on the processed data. Apart from data warehousing, data cleansing and data transforming are also used for statistical and mathematical operations.

Difference Between Data Cleansing and Data Transformation

Definition

Data cleansing is the process of detecting and removing corrupted or inaccurate records from a record set, table or database while the data transformation is the process of converting data from one format or structure into another format or structure.

Usage

Furthermore, data cleansing helps to clean the dataset and improve the data consistency while data transformation helps to make data processing easier.

Conclusion

Data cleansing and data transformation are two techniques used in data warehousing. The difference between data cleansing and data transformation is that the data cleansing is the process of removing unwanted data from a dataset or database while the data transformation is the process of converting data from one format to another format.

Top 6 Digital Transformation Trends in Hospitality and Tourism

In the past few months, we’ve been looking at digital transformation trends in different industries like healthcare, retail, finance, and media and entertainment. Today, we look at an industry that’s been completely turned on its head in recent years, due to extreme digital transformation: tourism and hospitality.

It used to be that we’d visit a brick-and-mortar travel agent every time we needed to plan a family vacation or work trip. (Granted, some of you may not remember that.) But today, thanks to mobility, travelers are playing a much larger role in the experience. They want to find a hotel that matches their style—on their terms—the very moment they need it. And thanks to players like AirBnB, which set the stage for a completely new era of travel, they can. Indeed, when it comes to the hospitality business, digital transformation is a mix of greater customer demands—and the technology that can help meet them. Let’s take a look at the top trends impacting the hospitality and tourism industry.

 

Mobile Integration

The digital transformation is a dream come true for introverts who like to travel. With mobile-first and mobile-only brands continuing to grow, customers can do practically anything on their phone, from checking in—to ordering room service—to unlocking the room door itself. In fact, one can plan an entire trip—from booking to bedtime and home again—without ever talking to a live human.

AI and Chatbots

Remember when all hotels used to have clunky welcome binders on the desks, outlining where to eat, what to see, and what to do in the area—everything you needed to know? Today, hotels can provide all that information—and more—via AI-powered apps and technology. Guests can access the information at any time they need, right from their phones in the form of an e-concierge. They can even access voice-activated chat bots to open the curtains, set the alarm, or order breakfast, without ever talking to a human being. At the Cosmopolitan in Las Vegas, you can even text a robot named Rose at any time, 24/7, and she’ll find a way to fill your request, fast. Meanwhile, Marriott has been using AI-powered chat bots at nearly 5,000 hotels to do things like make reservation changes, and check on account balances or redemption vouchers.

Integration of the IoT

As more and more devices get connected to the Internet of Things (IoT), it makes sense that the tourism and hospitality industry would begin to harness that data to improve the customer experience. After all, the more they know about their guests, the better they can please them. If the IoT data tells them the customer has visited their resort every year for the last three years, it can automatically send a message proactively asking the guest if they’d like to make another booking this year. You just saved your customer a step—and guaranteed a booked room—without ever lifting a finger. The same could be said by harnessing information about food selection, excursions, and in-room amenities. The opportunities for up-sells and better CX are endless.

Focus on Data

As noted above, data is going to play a huge part in the new era of hospitality and tourism. In the case of AirBnB, they were able to use customer data to determine that guests who chose not to book were doing so because they were discouraged by hosts who failed to respond to their inquiries. (I’ve been there—it’s annoying.) By offering instant booking feature to guarantee their reservation, they helped alleviate many of the customers’ concerns and helped automate what had previously been an incredibly arduous part of their business model. Data didn’t just improve CX. It improves the bottom line, as well.

Reputation

The fact that guests can book instantly also means they can share their opinions instantly via Facebook, Yelp, TripAdvisor and other travel review websites. That’s why technology has pushed hotels and restaurants to focus even more on providing quality customer service. Yes, there are outliers. I’ve experienced them myself. But there is no doubt the trend is toward better service for guests—not just a better return for operators.

Virtual Reality

Whether it’s a hotel property, museum, or a tourist destination, guests can take a look without even leaving their living room via virtual reality. The goal is either to offer a preview of what guests will experience—or offer the next-best-thing to visiting at all. (For instance, would you rather pay $4,000 to visit Paris in real life, or $200 to take the same trip in a virtual world?) This isn’t being done on a widespread scale yet, but some major operators are offering guests the chance to experience at least a snippet of their travel experience—offering greater piece of mind especially to those planning a visit to a faraway destination. Others destinations, like the Museum of Modern Art in New York (MOMA) are already offering VR installations as part of  their exhibits.

The travel and tourism business is a $1.2 trillion industry. Clearly, there is incentive to invest to grow it even more. Whether the IoT is improving the accuracy of flight schedules, or the lure o f VR is convincing someone to take their first overseas trip, there is truly no end to the value tech can add to travel. They just need to be careful it doesn’t become so good that guests prefer the tech over the real thing.

References

1)Lithmee(2018)’Difference Between Data Cleansing and Data Transformation’.Avaliable at:

https://pediaa.com/difference-between-data-cleansing-and-data-transformation/

(Accessed:25 March 2022)

2)Newman,D.’ Top 6 Digital Transformation Trends in Hospitality and Tourism’.Avaliable at:

https://www.forbes.com/sites/danielnewman/2018/01/02/top-6-digital-transformation-trends-in-hospitality-and-tourism/?sh=ba27d5567df1

(Accessed:25 March 2022)


Anil(10598717)


KeyWords:#travel#budget#revolution#social#socialmedia#Data#Industry#BigData#World#Marketing#Extension#Hotel#Tourism#Cleansing#Transformation

3 comments:

  1. Thats the amazing topic to learn Cleansing and Data

    ReplyDelete
  2. That is very useful topic to find difference between cleansing and transformation

    ReplyDelete
  3. It's a really helpful article. I was wondering about veracity cleansing and data, I can see how is important for businesses. There are lots of benefits to help the process of data transformation. Also, virtual reality technology helps a lot of customers and business owners. It gives the opportunity for the guest to visit different places all around the world without paying too much cost. I believe, in the future, every single person will experience it. But some people prefer to visit places in reality.

    ReplyDelete

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