Big Data Storage: What You Need to Know

Big Data Storage: What You Need to KnowToday, businesses have to grapple with vast amounts of data from different sources, including emails, mailing lists, customer orders, system logs, mobile apps, social media networks, etc. This data is crucial to businesses in various ways. When analyzed, a business can identify operational issues, personalize the customer experience and manage supply chains – all contributing to better decision-making.

However, big data also has challenges, especially regarding its storage due to size and other factors such as collection speed, processing, retrieval and format. This becomes more complicated as the data keeps growing with time and cannot be stored in traditional storage devices, necessitating a need for facilities that store and process the data efficiently.

Depending on the business type, a choice can be made between storing data in a warehouse or in the cloud. A data warehouse is a building facility that stores and processes data for a business. This in-house data storage offers the advantage of speed. However, when more space is needed, it will be necessary to acquire more physical storage.

On the other hand, a business may choose to opt for cloud storage. Cloud storage offers the benefit of convenience, accessibility, cost and maintenance, which the service provider handles.

Considerations in Storing Big Data

Regardless of the means a business chooses to store its data, there are various issues to consider:

  • Understand your data – before choosing a data storage method, it is essential to first understand the company’s data in terms of the type of data collected, quantity, storage period, retrieval speeds, use cases, etc. This helps choose a data management system that can handle the data efficiently.
  • Data governance – with so much data collected and with data growing exponentially, it is likely that users can be lost in a sea of data. Therefore, a business should define a strategy that aligns with business goals to avoid collecting unnecessary data that takes up storage space.
  • Data integration tools – data is collected from multiple sources, and it is necessary to have adequate integration tools that allow for different file formats.
  • Cost – it is difficult to determine the actual cost of storing data. Hence, a business should not base the cost decision on the upfront cost alone. This is because other factors are involved, including operating costs, the need for scalability, training or hiring users, new technologies, and the cost of backup. Businesses must evaluate whether the initial investment in the best data storage technologies is worthwhile by looking at the potential long-term results.
  • The data storage provider – before settling on a service provider, thorough research should be conducted. Some considerations when choosing from a variety of providers should include the availability of technical support to solve problems quickly, scalability, fault tolerance, pricing models, and reviews from existing customers.
  • Disaster recovery plan – ensure it is possible to recover data quickly. This is crucial with attacks that deny access to data without paying a ransom. A business should consider keeping secure offsite backups.
  • Enhanced security is required – the expanding IoT network adds to the number of endpoints and devices storing or retrieving data. Therefore, big data comes with a huge responsibility to preserve data in an environment where hackers are pervasive and never stop coming up with new ways to break into systems. It is recommended to choose the safest option even when it costs more, as data security is vital for the survival of any business.
  • Employee training – big data may require a business to hire new staff to help in analytics, such as data scientists. Regardless, a business should consider training existing employees on handling big data and using new tools that will be introduced. Big data also requires collaboration among different departments in an organization. Data-literate employees can better interpret data, ask the right questions, and generally make data-driven decisions.

Compliance with data security regulations – this especially applies to highly regulated industries such as finance or health. It is essential to ensure that even when outsourcing data storage and management, the service provider adheres to compliance regulations to avoid heavy fines that come with a violation. 




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