How can businesses solve the challenges they face today in big data management?
One could argue that the value of good big data management is more important to the business during times of uncertainty than compared to when times are great.
Sound decisions are even more critical to the business survival, and to do so you need a high level of data quality and accessibility more than ever.
Providing this can help identify new opportunities for additional revenue as well as reducing costs, creating a more agile organization.
During this uncertain time, IT is responsible for maintaining much of the company’s “sense of normalcy,” by supplying their company’s workforce with the best hardware, software and collaboration tools to securely work remotely and monitoring them for security issues or vulnerabilities.
Efforts to solve big data challenges do not have to come to a complete stop because workers are working remotely more, and although reduced budgets will certainly have an impact on overall scope of possible solutions, there are still opportunities to explore.
Fortunately advances in big data management within the cloud minimize the two biggest barriers to entry: cost and accessibility.
Independent of your company’s current stage of analytical maturity, remote applications built to manage big data can be spun up very quickly in a serverless cloud architecture, and at a fraction of the cost when compared to an on-premises model.
With some cloud platforms like AWS and Azure, you have at your disposal the complete stack of big data management, individual services that can help manage governance, security, data quality, storage of extremely large data sets, data warehousing, data lakes, dashboarding, machine learning, AI, and forecasting.
This complete set of integrated "building blocks" allows users to simply turn on which components they want to experiment with or leverage in a production capacity, and just as easily turn off to minimize cost.
It’s a fantastic model because it allows smaller companies with minimal analytical capabilities to experiment and scale at a minimal cost, while also being able to handle companies with extremely large data volumes that want to answer complex questions analyzing unstructured data.
It can help create efficiencies and greatly extend capabilities while we collectively navigate these uncertain times.
More Q&As from our experts
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