Conversations on the Internet produce massive amounts of unstructured data. It’s important, therefore, to define what the goals are for a social media listening initiative. Depending on the goal, the right tool might be a series of free Google Alerts or an expensive software suite. That eventually, includes ad hoc analysis and full integration with legacy customer relationship management (CRM) applications.
Both social media and person-to-person information-gathering have value, but social media listening is quickly becoming an important customer intelligence tool. There are several ways to use social media to gain insight. After all, which usually provides a massive but valuable unstructured data.
Including, monitoring online customer support forums, and using software tools to gather comments from social outlets. Such as Facebook and Twitter and encouraging customers to suggest new product features and vote on their favorites.
Not to be dramatic, but digital marketers today live and die by the tools of the trade. Whether we’re digging through data or fine-tuning our social presence, relying on the right digital marketing tools means saving time and maintaining our sanity.
What Is The Unstructured Data Meaning?
Generally, the phrase ‘Unstructured Data’ usually refers to information that doesn’t reside in a traditional row-column database. As you might expect, it’s the opposite of structured data — the data stored in fields in a database. Unstructured data files often include text and multimedia content.
Examples include e-mail messages, word processing documents, videos, photos, audio files, presentations, webpages and many other kinds of business documents. Note that while these sorts of files may have an internal structure, they are still considered “unstructured” because the data they contain doesn’t fit neatly in a database.
Experts estimate that 80 to 90 percent of the data in any organization is unstructured. And the amount of unstructured data in enterprises is growing significantly — often many times faster than structured databases are growing.
Important to realize, structured data generally resides in a relational database, and as a result, it is sometimes called relational data. For example, a database designer may set up fields for phone numbers, zip codes and credit card numbers that accept a certain number of digits.
Why Does Unstructured Data Matter?
Because 80% of the data in companies is unstructured, organizations need to understand the types of unstructured data they are accumulating. And the best ways to process and store this data for business advantages. Without data management strategies and guidance in these areas, companies run the risks of not capitalizing on it.
In the end, failing to keep up with competitors, or storing more unstructured data than they really need, thereby running up data center costs. As an example, every x-ray or MRI image for a patient is related back to the patient’s record in the hospital’s record system. And this is one of its values: It enriches corporate data and enables leaders to work smarter.
Not to mention, it can affect everyone at the company, from the entry-level staffer to the CEO. Many industry watchers say that Hadoop has become the de-facto industry standard for managing Big Data. This open-source project is managed by the Apache Software Foundation.
Using The Mined Data
Internally, almost every corporate department uses unstructured data in some form–from engineering with its raster drawings to marketing with its social media engagements and photo imagery, to financial and office operations with scanned documents.
Externally, it is used to monitor and report on movements of shipments and/or assets with sensors. As well as, monitoring school campuses with security cameras, and to exchange videos, photos, images, audio transmissions, etc. with suppliers and other business partners.
On the other hand, social listening is also common in data mining. Social Media Listening, also known as Social Media Monitoring, is the process of identifying and assessing what is being said about a company, individual, product or brand on the Internet. Not forgetting, conversations on the Internet produce massive amounts of unstructured data.
We’ve set out to put together a list of tools that are valuable to marketers of all shapes and sizes. After all, it doesn’t matter if you’re on a pint-sized team or you’re looking for enterprise-level digital marketing tools–this all-inclusive list has you covered.
How Do You Mine Unstructured Data?
In reality, many organizations believe that their unstructured data stores include information that could help them make better business decisions. Unfortunately, it’s often very difficult to analyze it. To help with the problem, organizations have turned to a number of different software solutions designed to search unstructured data and extract important information.
The primary benefit of these tools is the ability to glean actionable information that can help a business succeed in a competitive environment. Because the volume is growing so rapidly, many enterprises also turn to technological solutions. In that case, to help them better manage and store their unstructured data.
These can include hardware or software solutions that enable them to make the most efficient use of their available storage space.
How Do You Manage Big Data?
In addition to structured and unstructured data, there’s also a third category: semi-structured data. Semi-structured data is information that doesn’t reside in a relational database but that does have some organizational properties that make it easier to analyze. Examples of semi-structured data might include XML documents and NoSQL databases.
The term big data is closely associated with unstructured data. Big data refers to extremely large datasets that are difficult to analyze with traditional tools. Big data can include both structured and unstructured data, but IDC estimates that 90 percent of big data is unstructured data. Many of the tools designed to analyze big data can handle unstructured data.
Organizations use various software tools to help them organize and manage unstructured data. These can include the following:
1. Big data tools
Software like Hadoop can process stores of both unstructured and structured data that are extremely large, very complex and changing rapidly.
2. Business intelligence software
Also known as BI, business intelligence is a broad category of analytics, data mining, dashboards and reporting tools that help companies make sense of their structured and unstructured data for the purpose of making better business decisions.
3. Data integration tools
These tools combine data from disparate sources so that they can be viewed or analyzed from a single application. They sometimes include the capability to unify structured and unstructured data.
4. Document management systems
Also called enterprise content management systems, a DMS can track, store and share unstructured data that is saved in the form of document files.
5. Information management solutions
This type of software tracks structured and unstructured enterprise data throughout its lifecycle.
6. Search and indexing tools
These tools retrieve information from unstructured data files such as documents, Web pages, and photos.
Unstructured Information Management Architecture
By definition, Unstructured Information Management Applications are software systems that analyze large volumes of unstructured information. Particularly, in order to discover knowledge that is relevant to an end-user. As an example, an Apache UIMA might ingest plain text and identify entities, such as persons, places, organizations; or relations, such as works-for or located-at.
For instance, a group called the Organization for the Advancement of Structured Information Standards (OASIS) has published the Unstructured Information Management Architecture (UIMA) standard. Notably, Apache UIMA is an Apache-licensed open-source implementation of the UIMA specification [pdf] [doc].
That specification is, in turn, being developed concurrently by a technical committee within OASIS, a standards organization. They invite and encourage you to participate in both the implementation and specification efforts. Here: Welcome to the Apache UIMA project
How Does UIMA Operate?
The UIMA defines platform-independent data representations and interfaces for software components or services called analytics. All in all, which analyze unstructured information and assign semantics to regions of that unstructured information.
UIMA enables applications to be decomposed into components, for example “language identification” => “language-specific segmentation” => “sentence boundary detection” => “entity detection (person/place names etc.)”. Each component implements interfaces defined by the framework and provides self-describing metadata via XML descriptor files.
The framework manages these components and the data flow between them. Additionally, UIMA provides capabilities to wrap components as network services. And also, can scale to very large volumes by replicating processing pipelines over a cluster of networked nodes.
We hope the above guide was helpful in your preparation for your brand, business, or even product data mining. But, if you have additional information, contributions, or even suggestions that demand our attention, please get in touch with Us. You can share your thoughts in the comments section below. All in all, below are more useful and related topic links that might best interest you.
- Unstructured Data: A Cheat Sheet
- Structured Data Schema Markup Design For AMP Rich Snippets
- Donut Charts | How They Help In Visualizing Real Data Stats
- How AI Analytics & Machine Learning Algorithms Simplify Data
- How To Increase Social Media Engagement Rate