Enterprise Data (And How To Collect It With Web Scraping)
Data is the lifeblood of any organization today, profit or non-profit, small, medium, or large. Enterprise data is the sum total of data that you generate, share, and utilize in your business. And you simply can’t do without it. Every business decision you make or will make depends on the data available to you. Take, for example, you want to start promoting your business through a new channel, say, social media. You have to gather data on different social media platforms, analyze the type of people that use each platform, decide the ones that contain your ideal customer before you can make the decision. And that’s for something as straightforward as a new advertising channel. The importance of data for your business simply can’t be overstressed.
As more and more people realize this, there has been an increasing urgency to collect, organize, manage, and utilize data properly by businesses and organizations. However, while small businesses can get by with traditional data management practices, if you have a big operation, you have to take a more structured approach towards managing your data. According to Gartner, the role of Chief Data Officer “will be a mission-critical function comparable to IT, business operations, HR, and finance in 75% of large enterprises” by 2021. This means that as a company, you have to have a whole department managed by a C-suite executive dedicated to gathering and managing data for you. That is how important this kind of data has become.
Despite the increasing consciousness of businesses on the need to effectively manage their data, they still face significant obstacles. These include how to source and properly collate data without redundancies or collecting irrelevant data. You are probably facing these issues too.
In this article, we’ll explore what exactly constitutes enterprise data, reasons why you need an data strategy, and how to use web scraping to source for and collect your enterprise data. Feel free to use the table of contents to navigate to whatever section you are most interested in.
Table of Contents
What Is Enterprise Data Management?
Before we go into this kind of data management, first, let us define this term. Data for enterprise purposes includes every single piece of data being collected, produced, shared, and utilized by your business. Customer data, market trends, financial data, legal data, product data, competitor research data, everything.
This data is divided into two categories: internal and external. Internal data is the data you generate within your company from day-to-day activities. External data is gathered from outside the company’s activities, such as competitor research data, consumer trends, etc.
From that, we can define this kind of data management as the process of collecting, collating, standardizing, and storing both internal and external data. It also involves making the data readily available to your employees and your customers when and where they need it. With the increasing digitization of business practices, more and more data is being produced every day. A plan is required by businesses to properly manage and properly utilize the relevant parts of the data available to them. And also discard the data’s irrelevant aspects. This kind of data management is the process of formulating that plan. The plan so formulated is what is known as a data management strategy.
The best strategy
An enterprise data strategy is a roadmap of how you collect, collate, store, and distribute your data. A data strategy defines the framework of your company’s relationship with data. While different companies will tailor their data strategy to their individual needs, there are a few things that a good data strategy should do:
- Define the company’s business goals and the data resources needed to meet those goals
- Determine the technical capabilities required to acquire the needed data
- Identify the structural and functional changes the company needs to make to use the data gathered effectively
- Set out a timeline for achieving the outlined goals
- Establish a plan for distributing the collected data easily
Web Scraping and Enterprise Data Management
Why is web scraping essential for the process?
The first problem you encounter in managing your data is how to get it and how to collate it into a meaningful format.
Web scraping uses automatic bots called spiders to crawl web pages, extract information from the web pages, and present the information in a useful format.
I don’t know about you, but that looks like a problem and its solution to me. Web scraping provides a straightforward and efficient means to gather data and organize it. While the data extracted by web scrapers can be possibly be collected manually, it would take forever. Also, manually gathering data will lead to getting banned from the data sources, but scraping bots bypass this by using multiple IP’s to request information from the sources. With the high volume of data a company requires to deploy an effective data management strategy, web scraping is the most viable solution to obtain your data and classify it in the shortest possible time.
Integrating web scraping into your data strategy
One of the most obvious benefits of integrating web scraping into your data strategy is its impact on data integration. This kind of integration involves collating and merging disparate data sets from different sources, reconciling it, standardizing it, and making it available in an easy-to-use format. Manual data collection usually poses a big problem for data integration processes, as most hand-collected data are unstructured and completely unusable. Data collected through web-scraping, on the other hand, comes in a structured format.
Also, since you specify the type of data you are looking for before putting a scraping bot to work, web scraping rarely produces irrelevant data. Using web scraping to gather data bypasses the entire processes of cleaning up data, categorizing it, and making it presentable. This eliminates some steps from your integration process and saves much time, energy, and expenses. Also, the data scraped can easily be repurposed and reused.
Having seen the benefits of using web scraping to collect data, let’s take a look at how to go about using web scraping to gather data.
Sourcing Your Enterprise Data With a Web Scraper
Using a web scraper is easy and fairly straightforward. Scraping the web is as simple as inputting a URL, clicking ‘Scrape,’ and downloading your data once the scraping is done.
However, to effectively employ web scraping to collect data, you must define your data requirements and parameters. One way to do this efficiently is by building a data model. These models are an aggregate view of the overall data processes, uses, and consumption of a company. Not to be confused with a data application model, an enterprise data models focus on business needs rather than the technology or application of the data.
Building a data model allows you to define the data concepts that are important to you and how different concepts from different departments overlap. This gives you a roadmap of the kind of data you need to make business decisions. Once you’ve determined the type of data you need and the data parameters, all you need to do is subscribe to a web scraping service like Scraping Robot. If you have the necessary infrastructure, you can build your own scraping bot. It is much easier to subscribe to a web scraping service, however. They provide all the backend support. All you have to do is input your data requirements and parameters, and the bots will scrape and organize your data. Most web scraping services have a tutorial that walks you through a step-by-step process of scraping the web.
Barriers To Using Web Scraping as an Enterprise Data Solution
With the ease of collecting data with web-scraping comes a few problems, including:
- Data quality assurance: One major problem of scraping the web for data, especially at the volume required by companies, is data quality. A small deviation in your data’s correctness can lead to enormous consequences for your business at high volumes. The best way to improve data quality is to have clearly defined requirements and parameters. This reduces the chance of unrelated or irrelevant data being scraped.
- Expensive: Scraping the web can be quite expensive, especially if you decide to build your own scraping infrastructure.
- Legal complications: With a bevy of regulations coming up on the use of data, the possibility of offenses like privacy violation, insider trading has increased dramatically. This necessitates using a data extraction solution that can mitigate these risks and keep your data within the bounds of legality. Most current web scraping services only have slight structures in place to deal with these risks.
Using Scraping Robot as Your Enterprise Data Resource
Scraping Robot offers a revolutionary approach to web scraping and data gathering by using APIs to submit scraping requests. This allows you to automatically submit scraping requests in real-time, instead of manually entering each page you want to scrape. Scraping Robot’s APIs automatically submit requests for relevant data every 60 seconds, providing you with real-time data without manually checking the pages. The use of APIs allows Scraping Robot to increase data quality by keeping up with changes in the web pages’ infrastructure being scraped, changes that could affect data quality.
Perhaps the most remarkable aspect of Scraping Robot is the low cost of running data scrapes. When you sign up for Scraping Robot, you get 5000 free scrapes. Every scrape after that costs only $0.0018. That is an incredibly low cost to pay for the quality of data gathered using Scraping Robots web scraping bots. If you want to get an idea of exactly how much you need to budget to cover your scraping costs, check out our pricing page
If you do not see a fit among our current modules for your needs, you can contact our developers’ team to design a custom module tailored to your needs.
Final Thoughts
Collecting and organizing your data properly to inform the right business decisions is a daunting task at the best of times. The ability to automate data collection and sharing can make all the difference between a successful company and an unsuccessful one. If you cannot gather timely data on what your competitors are doing, for example, there is a high chance you’ll be lagging behind the industry curve. And you could get pushed out of business by your competitors who are able to gather data on what you are doing.
Lucky for you, Scraping Robot offers an affordable and efficient way to collect data in a readily available and easy to use format. Managing enterprise data is slowly becoming more straightforward, but Scraping Robot has jumped the gun and made it easy as possible. So what are you waiting for?
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