One of the major challenges companies face is trying to harness unstructured data – digital information that can’t be stored efficiently in relational databases because it doesn’t use pre-set data models. Most companies have been accumulating massive amounts of unstructured data, including images, audio or video clips, emails, social media, documents, and more for years. As such, they’re sitting on a treasure trove of data that they’re not putting to good use.
All this data contains valuable information that can help organisations make better, more informed business decisions, enhance their processes and products, and operate more efficiently. However, because of the sheer volume, variety and velocity of unstructured data, organisations often find it difficult to uncover the insights they need to make the best business decisions. Additionally, the quality of this unstructured data is not as good as the quality of structured data, which means companies need to clean and enrich it to make it usable.
Challenges of Unstructured Data Management
Managing unstructured data presents several significant challenges for companies:
- Data Silos: Each department or team often collects and stores its data in different formats and systems, leading to data silos. This fragmentation hinders quick and efficient access to data across the organisation. To overcome this, businesses should aim to centralise their data storage, enabling seamless access and collaboration.
- Data Quality: Unstructured data usually requires extensive cleaning and preparation before it can be effectively organised and analysed. The sheer volume of unstructured data can make this task daunting, yet data cleaning is important to realise the full value of the data. Companies must invest in robust data cleaning processes to ensure high-quality, usable data.
- Data Storage Costs: As the volume of unstructured data grows, so do the costs associated with storing it. Organisations need to find ways to manage these costs effectively. One solution is to compress data, which reduces the amount of storage space required. By minimising storage needs, companies can manage their data more efficiently and keep costs under control.
Why Companies Should Manage Their Unstructured Data
Effectively managing unstructured data allows companies to extract valuable insights, enhance productivity and drive business opportunities. Managing unstructured data efficiently ensures that employees can easily locate and access the information they need, boosting overall productivity. Real-time analysis of unstructured data helps organisations quickly identify and address critical issues, while keeping data organised and up-to-date aids in maintaining compliance with industry regulations.
In essence, a strong data management strategy enables companies to maximise the value of their unstructured data, turning it into actionable insights that support informed decision-making and foster business growth.
To achieve this, companies should focus on understanding, cleaning, enriching, organising and using standards-based tools to manage their unstructured data effectively.
Ways to Manage Unstructured Data
Implement Robust Data Governance
Data governance is the foundation for managing unstructured data. It involves establishing policies, procedures and standards to ensure data quality, security and compliance. A robust data governance framework helps in defining who can access data, how data should be handled, and what measures should be in place to protect sensitive information.
To implement effective data governance, organisations should:
- Create a data governance team: Form a team comprising members from different departments, including IT, legal, and business units. This team will be responsible for defining data governance policies and ensuring compliance across the organisation.
- Develop clear policies and procedures: Establish clear guidelines for data access, storage and usage. These policies should address data privacy, security and compliance with regulations.
- Use data governance tools: Invest in data governance tools that automate policy enforcement, monitor data usage and provide insights into data governance activities.
Leverage Advanced Analytics and AI
Advanced analytics and artificial intelligence (AI) can play a significant role in managing unstructured data. These technologies help in extracting valuable insights from unstructured data, making it easier to analyse and utilise.
- Natural Language Processing (NLP): NLP algorithms can analyse text data, identify patterns, and extract meaningful information. This is particularly useful for processing large volumes of text data from sources like social media, emails, and customer reviews.
- Machine Learning (ML): ML models can be trained to recognise patterns in unstructured data, such as images and videos. These models can automate tasks like image recognition, sentiment analysis, and anomaly detection.
- Data Visualisation: Advanced analytics tools offer data visualisation capabilities that help in presenting unstructured data in a more understandable format. Visualisations like word clouds, heat maps, and network graphs can reveal hidden patterns and trends.
Utilise Data Lakes
A data lake is a centralised repository that allows organisations to store all their data, both structured and unstructured, at any scale. Data lakes enable organisations to keep unstructured data in its raw form until it is needed for analysis, providing greater flexibility and scalability.
- Scalability: Data lakes can handle massive amounts of unstructured data, making them suitable for organisations with growing data needs.
- Flexibility: Unlike traditional databases, data lakes do not require data to be organised in a specific format. This flexibility allows organisations to store a wide variety of data types.
- Cost-Effectiveness: Storing data in a data lake can be more cost-effective than using traditional storage solutions, especially for large volumes of unstructured data.
Adopt Metadata Management
Metadata provides context and meaning to unstructured data, making it easier to find, understand and use. Effective metadata management involves creating and maintaining metadata for all unstructured data assets.
- Metadata catalogues: Develop a centralised metadata catalogue that indexes all unstructured data assets. This catalogue should include information such as data source, format, creation date and usage history.
- Automated tagging: Use automated tagging tools to generate metadata for unstructured data. These tools can analyse data content and automatically assign relevant tags, reducing the manual effort required.
- Metadata standards: Establish metadata standards to ensure consistency and accuracy across the organisation. Standardised metadata makes it easier to integrate and analyse data from different sources.
Ensure Data Security and Compliance
Unstructured data often contains sensitive information, making security and compliance critical. Organisations must implement measures to protect unstructured data from unauthorised access, breaches, and regulatory non-compliance.
- Data encryption: Encrypt unstructured data both at rest and in transit to protect it from unauthorised access. Encryption ensures that even if data is intercepted, it remains unreadable without the decryption key.
- Access controls: Implement strict access controls to ensure that only authorised users can access unstructured data. Role-based access control can help in assigning permissions based on user roles and responsibilities.
- Compliance monitoring: Regularly monitor unstructured data for compliance with relevant regulations. Use compliance management tools to automate the monitoring process and generate audit reports.
Due to its complexity, unstructured data, often overlooked, holds significant potential for driving key organisational decisions. As unstructured data is projected to double every two years, Komprise offers a solution to manage this rapid growth while keeping costs in check. If your business is interested in gaining control of your unstructured data, contact our team at IDS today.
