These days, every organization faces the biggest challenge of managing unstructured data, which is 80 to 90 percent of all enterprise data. This huge volume of digital data is quite essential for an organization because once it gets fully organized, it unlocks valuable insights to grow your business exponentially. Today, I am going to unlock the 6 most effective strategies for managing unstructured data.
But before I start explaining them, I would like to shed light on two crucial aspects:
1- What is Unstructured Data?
Unstructured data is a type of data that is not arranged as per preset models in databases. It is an amount of data that doesn’t fit in traditional databases. The best examples of unstructured data are social media posts, comments, emails, texts, surveillance data, etc.
2- Challenges of Managing Unstructured Data
Here are some main challenges every organization faces during unstructured data management:
- Volume
- Variety
- Costs
- Data Quality
- Compliance and Security
- Scalability
Now let’s dive them in detail:
Volume
As I told you before, this kind of data is around 80 to 90% of the whole data your organization has. Let’s say your organization has 500 employees with 10,000s of customers. You communicate with them through emails and imagine how many emails and texts you have to handle from time to time.
Customers connect with us through emails but they also send texts on WhatsApp. It’s hard to imagine the number of emails in almost a month. You can set up a structure for your emails. But what about data available on text messages? The huge volume of data is the primary challenge which you need to overcome through a reliable unstructured data management solution.
Variety
Unstructured data is available in a wide variety of forms and formats. You have to handle images, texts, files, emails, comments, videos, etc.
Now if you check there are many different formats of images such as jpg, png, jpeg, etc. Again other kinds of data have various forms. So, you need to organize your data in a way that it can handle different forms of your various data.
Costs
When it comes to unstructured data management, cost is indeed the biggest challenge. Organizations need to invest money in data stories, data analysis, or cloud solutions. Once you take into account the volume and variety of data, you have to invest big in all these management solutions.
It’s not that you will get one service and your whole unstructured data will be managed. At one point you need cloud solutions for data storage and recovery and on another point, you need analysis tools for getting valuable insights from this stored data.
Data Quality
When you have structured data, you set criteria and determine data quality and relevance. But this thing becomes tricky with unstructured data. It’s because this data has no standard format or schema. Unless you have advanced analytical tools for unstructured data, it becomes difficult to assess the quality of data.
Compliance and Security
Every organization has to comply with regulatory requirements. When it comes to compliance, you need to identify and protect sensitive information and data. Since data volume is huge, it will always be a challenge to retrieve or discover specific data from a varied dataset, unless your organization employs proper data discovery and classification tools.
Scalability
Whether an organization employs some tools or systems for unstructured data management, this tool should be scalable with ongoing data growth. Creating a scalable unstructured data management solution without any lack of performance is another challenge.
Best Strategies for Unstructured Data Management
- Data Identification and Categorization
- Implement Advanced Data Analytics Toolss
- Data Integration
- Use of Data Lakes
- Rely on Data Management Platform
- Data Quality and Governance Practice
Management of unstructured data is quite tricky due to its volume, variety and complexity. However, here are some right strategies that allow organizations to not only manage their unstructured data but also gain some valuable insight from it.
1-Data Identification and Categorization
The first strategy you can implement for unstructured data management is identification and categorization. You need to have a complete understanding of all kinds of unstructured data. For example, you can identify your data as emails, documents, files, videos, comments, social media posts. Once identification is done, the next step is categorization.
It’s easy to create categories based on content type and relevance. The purpose here is to ensure that you can store all the data efficiently while making the data analysis process as smooth as possible.
You can set some goals and then categorize the data based on these goals. For example, your business goal is to improve your customer service. Now you can categorize comments, customer feedback, and social media posts in a way that you find some positive and negative information related to your product and service. This categorization will aim to become familiar with customer complaints and feedback and then improve your product and service.
2-Implement Advanced Data Analytics Tools
Another strategy that helps you get insight from unstructured data while managing it well is the implementation of advanced data analytics tools such as Machine learning and Natural Language Processing.
You can implement NLP on social media posts and comments. Natural language processing lets you identify what your customer thinks and what the latest trends in the industry are. When you follow these trends, your company can easily stand out in the crowd.
Once you integrate your video data with Machine Learning (ML), it allows you to identify those patterns and trends in data that you can’t see otherwise.
Integration of Advanced analytics tools with unstructured data will make it easy for your organization to look deep into customer feedback and predict trends. In other words, you get a better understanding of available data to improve your product and make some informed decisions.
3-Data Integration
Another way to manage your unstructured data is to integrate it with structured data. You already have traditional databases in place. You need to combine data from different sources and take a holistic view of the information.
For example, you already have structured data in the form of the purchase history of your customer. Now when you want to gain insight into customer satisfaction and buying behavior, you can keep purchase history (structured data) alongside customer feedback/social media post comments (unstructured data), it’s how you can learn more about your customers.
When it comes to the integration of structured and unstructured data, you need to rely on the most effective data integration tools. Invest in those tools that can combine the data and then make it easy to access and accurate.
4- Use of Data Lakes
If your organization wants to manage unstructured data with a scalability option, data lakes always come in handy. They allow you to manage and analyze unstructured data without transforming it. This option provides you great flexibility as you can try different analytics applications for your unstructured data based on your business requirements.
5-Rely on Data Management Platform
These days, you can have your hand on a wide variety of data management platforms, which allow you to organize your unstructured data pretty well. You can store all your data in one place and access the files you need as and when you want. The best thing about such platforms is that they can handle a wide variety and forms of data and offer unstructured data management services to organizations of every size and scale.
They categorize all kinds of data, from text to multimedia, and make it easy and simple for your organization to find and access it. Another best practice of unstructured data management solutions is that they will archive inactive data to save the cost of data storage for the organization.
6-Data Quality and Governance Practice
Another effective strategy is to opt for data quality and governance practices for the management of unstructured data, which is usually inconsistent, messy, inaccurate and outdated. Data profiling practice is pretty common where data managers can examine the structure, content and metadata of unstructured data.
The purpose of this examination is to identify characteristics of data and it helps in proper categorization and management. Data cleansing is a process where unstructured data is completed and made accurate by removing any errors, missing values, duplicates, etc. You can manage data with data enrichment practice where you add or append additional information with unstructured data. Security of unstructured data is quite vital and thereby, your organization can manage unstructured data with the application of authorization, encryption and authentication techniques.
Wrap up
Management of unstructured data is not very simple. I explained all the challenges that organizations face during unstructured data management. Although the whole process is quite challenging, once you employ the right strategies for the management, then you can get valuable insight from this huge data. I have explained the six best strategies that organizations can implement to overcome challenges related to unstructured data. Relying on unstructured data management solutions is a cost-effective strategy, though. Don’t you think?
