Tag: UnStructured Data

What is Unstructured Data?

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.

Examples of Unstructured Data

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.

Mining Unstructured Data

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 unstructured data. 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 of unstructured data is growing so rapidly, many enterprises also turn to technological solutions 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.

Unstructured Data and Big Data

As mentioned above, unstructured data is the opposite of structured data. Structured data generally resides in a relational database, and as a result, it is sometimes called relational data. This type of data can be easily mapped into pre-designed fields. 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. Structured data has been or can be placed in fields like these. By contrast, unstructured data is not relational and doesn’t fit into these sorts of pre-defined data models.

Semi-Structured 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.

Unstructured Data Management

Organizations use of variety of different software tools to help them organize and manage unstructured data. These can include the following:

Big data tools

Software like Hadoop can process stores of both unstructured and structured data that are extremely large, very complex and changing rapidly.

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.

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.

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.

Information management solutions

This type of software tracks structured and unstructured enterprise data throughout its lifecycle.

Search and indexing tools

These tools retrieve information from unstructured data files such as documents, Web pages and photos.

Unstructured Data Technology

A group called the Organization for the Advancement of Structured Information Standards (OASIS) has published the Unstructured Information Management Architecture (UIMA) standard. The UIMA “defines platform-independent data representations and interfaces for software components or services called analytics, which analyze unstructured information and assign semantics to regions of that unstructured information.”

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.

I used referenced web site : webopedia.com

We have a few referrer link, like big data, hadoop, business intelligence etch.

You can see the post at below link;

http://www.webopedia.com/TERM/U/unstructured_data.html

Thanks for this post : Vangie Beal

What’s the Difference Between Structured & Unstructured Data

If left unmanaged, your data can become overwhelming, making it difficult to procure information you need when you need it. While software is designed to address archiving, e-discovery, compliance, etc., the overarching goal is most always the same: to make managing and maintaining data a  feasible task. In this post, you’ll see two types of data you’re accustomed to working with, paying close attention to the differences between structured and unstructured data.

Data Structured vs Unstructured Data

 

What is Structured Data?

Before getting into unstructured data, you need to have an understanding for its structured counterpart. Structured data (as explained succinctly in Big Data Republic’s video) is information, usually text files, displayed in titled columns and rows which can easily be ordered and processed by data mining tools. This could be visualized as a perfectly organized filing cabinet where everything is identified, labeled and easy to access. Most organizations are likely to be familiar with this form of data and already using it effectively, so let’s move on to the hotter question.

What is Unstructured Data?

Believe it or not, your database of structured information doesn’t even contain half of the information available for your use! Seth Grimes, a leading industry analyst on the confluence of structured and unstructured data sources, published an article that stated, “80% of business-relevant information originates in unstructured form, primarily text.”  This may seem like an outlandish percentage, but don’t jump to conclusions too fast. We’re just getting started.

Now that you have a grasp on structured data, it will be much easier to understand what unstructured data is. Unstructured data, usually binary data that is proprietary, is that which has no identifiable internal structure. It can be visualized as a level 5 hoarder’s living room; it’s a massive unorganized conglomerate of various objects that are worthless until identified and stored in an organized fashion. Once this organization process has taken place (through the use of specialized software), the items can then be searched through and categorized (to an extent) for obtaining insights. While data mining tools might not be equipped to parse information in email messages (however organized it may be), you may have very good reason to collect and categorize data from this source. This illustrates the importance and plausible breadth of unstructured data.

Email Has Structure, Right?

The term “unstructured” has faced major scrutiny for several reasons. One argument is that although some form of structure is not formally identified, it can still be implied and therefore should not be labeled as “unstructured.” The counter-point states that if data has some form of structure but is not helpful to the processing task at hand, it may still be characterized as “unstructured.” So, while email messages may contain information that does have some implied structure, we can label the information as “unstructured” because normal data mining tools aren’t equipped to parse it. Alas, both sides of the argument persist.

Unstructured Data Types

Unstructured data is raw and unorganized and organizations store it all. Ideally, all of this information would be converted into structured data however, this would be costly and time consuming. Also, not all types of unstructured data can easily be converted into a structured model. For example, an email holds information such as the time sent, subject, and sender (all uniform fields), but the content of the message is not so easily broken down and categorized. This can introduce some compatibility issues with the structure of a relational database system.

In case you’re still not quite sure what we mean, here is a limited list of types of unstructured data:

  • Emails
  • Word Processing Files
  • PDF files
  • Spreadsheets
  • Digital Images
  • Video
  • Audio
  • Social Media Posts

Looking at the list, you may be wondering what these files have in common. The files listed above can be stored and managed without the format of the file being understood by the system. This allows them to be stored in an unstructured fashion because the contents of the files are unorganized.

–

The big data industry is growing but the problem of unstructured data going unused has been identified by organizations. Better yet, technologies and services are being developed in reaction. Darin Stewart of InformationWeek said in a recent article about big data, “The age of information overload is slowly drawing to a close. Enterprises are finally getting comfortable with managing massive amounts of data, content and information. The pace of information creation continues to accelerate, but the ability of infrastructure and information management to keep pace is coming within sight. Big Data is now considered a blessing rather than a curse.”

I used source sherpa’s web site.

You can see this post on their website :

What’s the Difference Between Structured & Unstructured Data?