The word ‘data’ is a widely used word but unfortunately it is equally misrepresented. That’s why many company men find it difficult while scraping data to grow their business. Until you don’t know the difference between various data and data stores, you are not likely to get the utmost advantage of data scraping tools.
There are hundreds of tools available that will definitely scrape data as per your wish. But you should also know your area of interest and how you could leverage the extracted data for the benefit of your business.
One of the successful strategies to implement in business while structuring your sales schemas is to do analysis regarding with your competitor’s plans. This is required to know where you succeed and on which sections you need to speed up your plans to sustain your growth.
The best way for business research and analysis is to compare your product’s and service’s credentials with the products available at leading marketplaces like ebay and amazon.
Data can be scraped from Amazon in many ways, you can extract either a particular type of data belonging to a specific category of product, data of all products or the entire data of the website. Also these extracted data varies in their life span over the website. The choice for selection of data is completely depends upon user’s command.
But to command, you need to be wise and for that you need to have knowledge of what and how You are going to extract.
In this article, we will mainly look at the two over confused sources of data on Amazon,i.e, data at database and datawarehouse and how efficient use of tools like Amazon Data Extractor and Amazon WareHouse Scraper assist you in achieving your goal.
Why the terms get confused?
When two things are closely connected and crucial for each other’s implementation, they often get confused by users. Likewise, Database and Data warehouse are habitually used as two parallel terms. Though both the term are operated for data storage and retrieval, there lies some distinct differences between the two. The pivotal differences between two are:
- The duration of time data is being stored at these two locations.
- Interior structure to store data
- Distinct uses of data stored in them.
- Analysis purpose
- Types/ variations
- SLA ( Service Level Agreement)
Where Databases are used as data repository to store data, data warehouse refers to those repositories that store aged data.
Database stores recent data and Data warehouse stores venerable data
You can understand the distinctness between these two with the help of this example, suppose you have been writing diary every night since 5 years. In one diary you write about your day outs for a month. Once that get ended, you keep it on a rack. After 4-5 years you will have 48-50 diaries on the rack whereas there is certainly a diary on which you are still on. The diary on which you are writing is your database whereas the shelf is the warehouse.
If you have to look for any information of the current month, you will refer to this month’s diary. On the other hand if you want to look for aged details, you will refer to the shelf.
Similarly if you are planning to launch a new product on your website you can track the progress of the products belonging to the same niche on marketplaces like Amazon or eBay. You can use Amazon Data Extractor to scrape information from current database. The extracted data will be used for comparison and to route strategy for that product.
If you are planning to launch a new online store, you need more detailed and aged information. Like which kind of products were popular in last few years, are they still user’s favorite, what changes marketers brought in those products, etc. in this case, you need a scraper to harvest data from marketplaces like Amazon’s warehouse. You can use tools like AmazonWare House Scraper to serve your purpose.
Now let’s look at the striking features of these Data Scraping Tools.
Amazon Data Extractor harvests and arranges data into user specified format. The software does the arrangement in very efficient way that describes every viable details about the product to the user. The scraper also pull out all information including Website URLs, Model no., ASIN (Amazon Standard Identification Number), Title, address, Product Description etc.
This tool also pull out product’s information along with website URL, Model no, ASIN, product description, etc. the primary difference is, it can extract bulk of data from Amazon warehouse. These information are Implemented by users to locate and frame product’s shopping preferences. It also arrange the product information in a CSV document. It is convenient when you want to scrape colossal data as it eases users with ‘one click extraction’, they don’t have to search each product one by one.
Over To You:
I hope, now you are able to draw the line of difference between the terms, database and data warehouse. On the basis of your understanding, you can now select the best Data Scraping Tool to strengthen your business. Still, if you have some doubts, feel free to ask us in the comments below.