Source: Mindtree

“To find signals in data, we must learn to reduce the noise - not just the noise that resides in the data, but also the noise that resides in us. It is nearly impossible for noisy minds to perceive anything but noise in data.” 

When you have data, how do you study it?

How do you manage to retrieve insights from it?

Data mining is a process where it converts raw data into an accurate analysis. Say for example you have data that reveals how the clients purchasing patterns are whenever a new product has been launched. 

In this scenario, data mining can showcase the data with real figures and facts that would provide an insight into how you can improvise the future product launches. 

Apart from providing the right data, data mining also gives a prediction of how your next client preference would be years from now. For instance, say today clients are interested to purchase products which have all the relevant features in one solution, tomorrow they would expect something else from it, maybe additional features for a budget-friendly amount. This expectations phase as you’ve read can provide the expertise of how brands like yours can shape the features and pricing factors accordingly.

With data mining this is possible. 

Data mining is the 2019 solution to win over all client’s in a shorter time. With predictable outcomes and accurate patterns, brands can outsell competitors without even struggling.

For instance, today many clients would be fine with working semi-manually during any processes. But many years from now, they would prefer a complete automated process for all their repetitive and easy tasks to be conducted.

How would you know?

With the data you collect, data mining can sketch an analysis giving away the facts right in front of you. You can seek client's preferences now and what their opinions are for the future and plan your product creation accordingly. 

The outcome for such an action will be: 

1 . Taking the right measures when any client's preferences change

2. Before competitors can even research and plan on the new change, you will be selling clients the solutions they are expecting
3. Your brand will grow quicker in the market since it can cater to all the target audiences needs better
4. With data mining,  brands will be able to focus on creating and applying solutions that will work and guarantee exceptional results. 

Client's preferences, tastes, and choices change with every new trend. It’s hard to keep up and monitor constantly when such changes are taking place frequently. Even with the new changes, it would take much more time to adapt to it as well as learn from it and create a solution that will benefit clients. 

Hence, to avoid all the time consumption, data mining can be a great asset for any B2B brand. We live in 2019 and so it only seems ideal when brands like yours think smart ways to acquire solutions in a hassle-free manner. Data mining is an example of one such solution.

Source: JetRuby

 “Every company has big data in its future, and every company will eventually be in the data business.” – Thomas H. Davenport, American academic and author specializing in analytics, business process innovation, and knowledge management

If a brand isn’t making good use of the data available or isn’t making an effort to retrieve the data, don’t be surprised when the same brand starts crawling instead of running the long success route. 

Data mining is a great tool to create a compelling analysis that will guide brands towards a better selling position, but how will one be able to analyze if sufficient data isn’t at hand?.

The online world has data but not much that can answer all branding solutions. With the increase in online crimes and security becoming tougher than a wall, it will take the right measures to crack your brand into accessing delicious information which will soothe your brand’s appetite for the longer term. Which is exactly why data harvesting is required. 

Data harvesting goes by any name, data scraping, data extraction, and many others. This is a process that shares similarity with data mining but instead of the accurate presentation, it provides brands with information that can help predict the accurate analysis. 

For instance, you are a brand that has one product which is doing great in your community. Now you aim to target a bigger audience by creating another solution that would swoop the minds of your target audience. How would you be able to do that?

Your first step would be to research. Gather all the information required to make this product creation a success. But wait?

You just found out that another website has the information you require. You immediately go to access it but is blocked. The reason it can’t be accessed is because only authorized users can access it. Hence what do you do when you know for yourself how valuable that data can be for your brand?

Here is when data harvesting pops in. With great data harvesting solutions, you can extract that data, save it in your system and conduct your data mining activities without any hassle.

 How easy is that?

You now have the generic information and also the crucial information which will add enough weight for you to create a successful product solution.  

Data harvesting or data scraping has a lot of benefits:

1 . Extracting any form of information required from any sources

2. Extract information without having to cause any hindrance to any of the sources
3. Store information without any hassle and keep it for any future references
4. Having quality data that will help you in growing your brand much more higher and enhanced.
5. With data harvesting, conduct automated scraping of data no matter the number of times. 

As a brand, data harvesting can grab in a lot of benefits for the brand as well:

1 . Make decisions quicker and faster and with better clarity

2. Any team can take necessary actions without having to waste their time to research in detail
3. Outsell competitors much quicker since the data needed to conduct this action will be at hand
4. Will always be updated and on point about understanding the market changes
5. Cater to any client's exact needs without any struggles

Have an ocean of data available in the systems which can be monitored and then help in planning strategies accordingly.

Today many applications and tools are available which will help conduct data harvesting in a greater manner. The applications help conduct the extraction of data easily by simply clicking on the website you want to harvest and then begin the process and finally saving it in the system. To conduct this process more efficiently, it would be ideal to conduct this process with the support of a proxy server.

Proxy servers is an application which will help conduct data harvesting without revealing any identities. At times maybe scraping a particular website won’t be possible due to its strict access rules , but that shouldn't stop you from accessing that data. Hence to avoid this common error, using a proxy server while conducting this action will prove to be more beneficial and valuable for any brand. 

There are many proxy servers available in the market. Start utilizing the one which suits your needs. 

Since you now have enough information about what the above two terminologies mean, it’s time to understand the unique factors of data mining vs data harvesting.

Source: Fiverr

Difference between Data Mining and Data Harvesting

1. Data mining is the process of executing data into an analysis pattern for better client study 1. Data harvesting is the process of extracting data from websites to retrieve quality information
2. Data mining stresses more on creating an analysis chart so that brands can conduct necessary actions according to the behaviour patterns of clients. 2 . Data harvesting stresses more on finding data that will help brands to execute, improvise, learn and apply solutions that will cater to assisting their needs.
3. The main agenda of data mining is to create a solution which will matter or will alter in the next few years. 3. The main agenda of data harvesting is to collect information about clients whose behaviour pattern will help you better understand their needs
4. Data mining gives a predictive analysis. 4. Data harvesting gives solutions that are coming directly from the mouth of what clients are expecting.
5. Data mining provides a long term solution to assist clients fluctuating preferences. 5. Data harvesting provides solutions which are needed on the spot to assist clients
6. Data mining is an automated process 6. Data harvesting can be done automated or manually.
7. Data mining collects tons of data you have in hand and creates a clear report of what the next few years will be like with reference to clients. 7. Data harvesting extracts any data which you require so that you can easily have it in your system to keep a closer check on. 
8. Another word for data mining is knowledge discovery in database. 8. Another word for data harvesting is data scraping.
9. With data mining, algorithms are used so that valuable data can be easily structured. 9. With data harvesting, the process is simple. You just need to click on the website which you want to scrape data from and the process begins henceforth.
10. A team of experts is required to conduct efficient data mining processes. 10. Data harvesting doesn’t require expert’s attention, even a beginner can conduct this process without any hassle.
11. Data mining tools: Rapidminer, Orange, Weka, KNIME and Sisense (top 5) 11. Data harvesting tools: Import.io, OutWithHub, Octaparse, Visual Web Ripper and Web scraper (top 5)