Data management involves acquiring, storing, securing and analysing an organization’s data to derive effective business intelligence from it. It includes all the procedures, tools and regulatory policies that govern data collection and analysis.
To derive usable insights, the quantities of data analysed must be quite massive. And organizations are doing just that, they are acquiring and storing data at a tremendous pace and quantity. Managing such data is a challenge and requires organizations to have appropriate systems in place.
Cloud solutions hold the key to this challenge. An effective cloud solution can manage data at scale without any drop in performance. It is equipped with the right computing power, is scalable, reliable and transparent.
Structured and unstructured data
Data management issues are more common when handling unstructured or qualitative data. Such data is not organised systematically and cannot be stored in predefined database formats. Prominent examples of unstructured data include satellite visuals, surveillance imagery, emails, images, audio and video files, social media postings and mobile text messages, among others. Almost all communication formats involve unstructured data. In fact, Gartner estimates that over 80 percent of an organization’s digital information is unstructured.
Structured or quantitative data on the other hand, can be stored in relational databases and is understood by machines. Algorithms and data mining tools can easily access and analyse such data.
Vulnerabilities of unstructured data
Unstructured data has several concerns because of its unorganised nature.
- The huge volumes of unstructured data make data verification with standard data analytics systems difficult.
- Reliability and security of the data are frequent problems.
The smart way to manage unstructured data is to move it to the cloud and take advantage of the many benefits such as flexible storage, scalability, cost savings and security. Organisations must carefully pick the right managed cloud service providers to enjoy the benefits.
Cloud as a data management partner
Unstructured data must be converted to structured data before it can be mined for insights but there are almost no straightforward tools to convert unstructured data to structured data. The data must first be analysed and sorted to some degree before it can be converted. Cloud-based ELT (extract, load, transform) tools can come in handy to manage the conversion. The structured data is ready to be analyzed for business insights by using artificial intelligence (AI) and machine learning (ML) tools and techniques.
High processing power for faster data analysis
The raw computing power of the cloud is exemplified through virtualization technology – where previously-isolated data is now part of a single, interconnected virtual environment and is automatically managed through virtual machines (VM). Using VMs, users can simultaneously run multiple operating systems on a single hardware machine and – saving load times and enabling faster data processing.
The high computing power can also handle ML technology that would automate the conversion of unstructured data into a structured form, making the cloud enhance the data management process to optimize both speed and accuracy.
As an example, one of our clients, a leading sports analytics company, had to manually compute data inputs and rank players/teams. Managing this unstructured data was time-consuming and difficult to consolidate for further analysis. This led them to seek an automatic process for the computation and ranking of players/teams.
To address these issues, we partnered with Microsoft Azure to implement a cloud solution that had an ML feature, Azure Machine Learning. This feature would automatically rank players and/or teams – thus, computing the metric data which would then be stored within the Azure Data Lake storage system. The predictive and automated nature of our solution resulted in our client making more timely decisions while saving on manpower.
Flexible data storage with more scalability
Cloud storage allows for data to be saved in off-site locations that can be accessed either through a private network connection or the public internet network. Businesses can easily scale their storage requirements on demand without having to buy or upgrade more hardware and software. This infinite scaling makes the data stored more resilient to physical disruptions while being easier to back up.
Additionally, cloud storage costs are only derivatives of the storage service used. Maintenance of the cloud servers and other associated infrastructures become the responsibility of the cloud provider, helping to reduce costs for businesses. Cloud storage provides an overall cost-effective and elastic storage outlet for data generated by businesses.
Higher data transparency and enhanced data security
Data and applications across multiple environments are secured through the system while allowing users to see all file activity. The cloud also has built-in security measures that alert both the user and provider about security threats or malware. Comprehensive security reduces the potential for data leaks and vulnerabilities, building customer trust and avoiding legal liabilities in the process.
Cloud is a comprehensive tool for data management
To sum it all up, the cloud addresses both front-end and back-end issues of data – providing businesses with an extensive solution for data handling. Data processing and analysis can be efficiently implemented through the sheer computing power of the cloud while security and storage capabilities are maximised through the cloud’s infinite scaling and built-in monitoring features.
