The amount of unstructured data that piles up in an organization makes it highly difficult for managing, thus leading to storage issues, compliance costs, and escalating corporate risks. Frequently, I’ve found organizing the data into analyzable information that can be utilized for business intelligence is restricted by elements like overheads, resources, and time.
According to Gartner analysts, the amount of unstructured information is predicted to go over 800 percent in about 5 years from now. With proper textual analytics, an unstructured text can be changed into a structured and more understandable data. I think that sums up on the vital nature of this analytics in managing unstructured information and their key roles in the running of an organization.
Manipulating Unstructured Business Data
The data that businesses use routinely including the spreadsheets, audio, video, log data, sensor data, external data and Power Point files are not stored in an orderly and standard database. In such a situation, I’d recommend using advanced business intelligence tools as the conventional forms will not work well here. The reason being they do not have that flexibility required to handle the amount of data accumulated and are also not equipped to support the latest analytical methods.
Risks Present in Management
Though analyzing data in the unstructured form is a definite solution, it does not give immediate results. The risks faced by organizations while analyzing include:
- Quality of data
- Categorization
- Relating the unstructured and structured data
- Processing a huge amount of information
I realize that this calls for technological upgrades like using BI, analytics or new databases. To enable this transition, businesses not only need the technological aid, but also need to understand what information they are searching for and what they want from it. Cloud computing for instance has opened up a new avenue for business to benefit from. Right from the customer service to the logistics planning, everything is managed appropriately and in real time too.
Leveraging Unstructured Information
Transformation of unstructured data into a relevant and structured format for use by businesses is enabled by text analytics. Analytics enables to process data in a broader sense, making it a powerful tool for businesses. Further, I’ve found that analysis of information is done in a better way with the help of tools like statistics, computational linguistics, and other fields in computer science.
Many a time, I’m confronted with people who mistake search for analytics. While search aids in document retrieval, analytics is information discovery that supplements the search. Combining the two enables improved classification and organization of documents and better interpretation. Analytics are highly beneficial for the unstructured information generated through customer comments, reviews, tweets, blogs, emails, call center logs, and documents present on the web.
What analytics accomplish?
Text analytics works on two major levels. One is organization of information and searching for content present within the documents. The other level, which I think is more vital, is finding about the emerging patterns and trends to get a better hindsight on the information.
Linguistic parsing, semantic analysis, and machine learning are used in analytics, producing highly useful applications like analysis of loan default, medical diagnostics and assessing of electronic information as proof in legal cases.
Sentiment analysis is another growing trend that enables understanding the customer comments, what analysts and important critics say about the services or products of a business. This type of analysis helps in gauging the positive and negative sentiments and lets you provide a better service.
Feedback analysis and unlocking the value of the feedback is possible only with text analytics, as it is humanly impossible to decipher free form text in a reasonable amount of time. With the analytics, one can predict what the customer will need in future with the data retrieved from the past. Analytics in short delivers value to information and enables extracting the insights present, which powers businesses towards a better performance.
The crucial factor that makes text analysis vital for business is its ability to get a deeper insight into the rationale of a solution. And in my opinion it also provides an understanding of what drives the statistics that emerge.
When an unstructured text is subjected to textual analytics, organizations can definitely benefit by the lowered risk and operational cost, and also by being able to make strategic and tactically sound decisions. Further, it also helps you decide on who would lead an organization in a better way.
