Continution to previous post - How to Address Big Data Challenges (PART 3 of 6)
Recruiting and retaining big data specialists
Finding and retaining individuals with big data expertise is one of the most difficult tasks in big data software development.
This big data craze isn't going away anytime soon. Cloud architects and data scientists are some of the most in-demand occupations in 2021, according to a survey from S&P Global. One way to fill them is to team up with software development services firms that already have large talent pools.
Working with HR to identify and fill any gaps in existing big data talent is another method.
Many big data projects fail due to inaccurate expectations and estimations that are carried over from the beginning to the finish. The right team will be able to assess risks, assess severity, and address a wide range of big data issues.
It's also critical to create a culture that attracts and retains top people. Hiring the proper people and establishing a safe business culture that keeps workers happy and engaged can bring you a long way.
Preventing out-of-control expenditures
The "cloud bill heart attack" is another prevalent big data challenge. Many businesses make the error of estimating the price of their new big data infrastructure using existing data consumption metrics.
One problem is that businesses misunderstand the enormous need for computing resources that increased access to larger data sets produces. The cloud, in particular, makes things simpler for big data platforms to surface richer, more detailed data, which can drive up costs because cloud systems can elastically extend to match user demand.
One problem is that businesses misunderstand the enormous need for computing resources that increased access to larger data sets produces. The cloud, in particular, makes things simpler for big data platforms to surface richer, more detailed data, which can drive up costs because cloud systems can elastically extend to match user demand.
When discussing big data deployments with business and data engineering teams, data management teams should bring up the cost problem right away.
It is the job of the business to identify what it is looking for; software developers should be in charge of supplying the data in an efficient format, and DevOps should be in charge of monitoring and managing the appropriate archival policies and growth rates.
To be continued... How to Address Big Data Challenges (PART 5 of 6)
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