When users contact the Astro team to buy residential IP addresses or search for the best datacenter proxies, most of them seek not only and not so much privacy. They seek what can be obtained with this privacy. Most of them want data. Today, we will discuss the difference between structured and unstructured data which is of importance if you are determined to be a data-savvy expert.
Definition of structured data
Structured data can be defined as a systemized and normalized format for quantity-related datasets. Such well-structured quantitative datasets, for their part, are subject to formatting by specifically designed and specified data management parameters. Normally, a typical format of this sort is shaped via Structured Query Language (SQL). The latter is responsible for deciding the format of fields as well as for the overall data model.
The basis of structured datasets is constituted by the link between stored pieces of info. These connections are also known as relational databases. Fields of such datasets are regulated by rigid formatting limitations. This fact is great for data searching and the application of various filters.
Great things concerning structured data
- Openness to cheaper ML tools. The strict specified parameters associated with such datasets greatly facilitates the work performed by ML-driven tools, as structured and well-readable content makes it easier for robots to identify logical connections and scrutinize the outcomes;
- Simpleness-to-comprehend for average users. Indeed, dealing with structured datasets does not necessitate deep knowledge of Big Data;
- Friendliness to multiple data harvesting tools, as most of them were built with a focus on structured data.
Instances and use cases
To get closer to reality, let’s cite some practical examples of structured data:
- Sales data;
- Payment details;
- Cell phone numbers.
Concerning use cases, the most self-evident are:
- CRM. A reliable data model can translate all the facts and figures into a clear picture of your customer’s behavior, preferences, and triggers;
- Inventory management when you collect all your or others’ flows to build projections;
- Finally, financial forecasts relying on harvested historical data are also an obvious example of models fueled by structured data. By the way, financial analysis and scraping of financial data is one of the key reasons why users contact Astro to buy residential IP addresses or purchase the best datacenter proxies.
Definition of unstructured data
Unstructured data denotes datasets notable for their one-of-a-kind unique formats, with no strictly predetermined storage properties. Datasets of this sort may contain heterogeneous pieces of info units in their unique native formats. As such, they are harder to research even though Data Science has already made significant progress in this path.
Great things concerning unstructured data
- A broad scope of potential insights. As long as types of unstructured datasets know no limits, obtaining an unstructured dataset grants different varying perspectives which may give birth to multiple insights;
- Quicker data collection is enabled by the absence of a predefined rigid format. Hence, it is much easier to collect such data in bulk.
Instances and use cases
- Comments and reactions left on social media. Pay attention, it is not about the number of comments, it is about their content and context;
- Media files, such as pictures, videos, GIFs, etc.;
- Documents in various heterogeneous formats.
Concerning possible use cases, one can name analysis of users’ behavior on social media platforms. With an advanced data model at your disposal, i.e. when one is capable of taking the context into consideration, you can understand a lot. Analyzing contexts is the key to gathering good insights from such findings.
Also, feeding unstructured data to chatbots to level them up is also a popular practice. However, neural networks have to be really powerful to handle this task.
Whatever kind of data you intend to harvest on the Web, Astro is ever-ready to support you! Buy residential IP addresses or the best datacenter proxies to collect any info you may require.