Close this search box.

AI & Data Best Practices

10 things to consider when implementing a big data platform

Table of Contents

Big data is a hot topic in today’s business world, and for good reason. With the right big data platform, companies can gain valuable insights into their operations and customers, leading to improved decision-making, increased revenue, and improved customer satisfaction. However, implementing a big data platform is not a decision that should be taken lightly. Here are 10 things to consider when implementing a big data platform.

Determine your specific business needs.

The first step in implementing a big data platform is determining what kind of data you’re looking to collect and analyze. Are you looking to track customer behavior on your website? Analyze social media sentiment? Understand your supply chain better? It’s important to have a clear understanding of what you want to achieve before moving forward with a big data solution.

Consider the scale of your data.

The sheer amount of your data will play a big role in determining the right big data platform for your organization. Will you need to store and process large amounts of data, or will a smaller solution be sufficient? Do you have a lot of streaming data and data in motion? 

If you’re dealing with large amounts of data, you’ll need a platform that can handle the storage and processing demands. Hadoop and Spark are popular options for large-scale data processing. However, if your data needs are more modest, a smaller solution may be more appropriate.

Check out our glossary entry on the Vs of big data.

Evaluate your current infrastructure.

Before implementing a big data platform, it’s important to take a look at your current infrastructure. Do you have the necessary hardware and software in place to support a big data platform? Are there any limitations or constraints that need to be taken into account? What type of legacy systems are you using and what are their constraints? It’s much easier to address these issues up front before beginning the implementation process.

Look into the different types of big data platforms available.

There are a variety of big data platforms available, each with their own strengths and weaknesses. Hadoop and Spark are two of the most popular options, but there are also other options such as NoSQL databases and stream processing systems. It’s important to evaluate the different options and choose the one that best fits your business needs both now and in the future.

Assess your in-house technical expertise.

Implementing a big data platform requires a certain level of technical expertise. It’s important to assess your in-house technical capabilities before moving forward. If you don’t have the necessary skills and resources, you may need to consider hiring outside help, outsourcing the implementation process, or hiring the skill sets necessary.

Consider the cost.

Implementing a big data platform can be expensive. It’s not just the initial cost you need to consider, but all the cost of hardware, software, and personnel. This can include the cost of purchasing or leasing new hardware, licensing software, and hiring additional staff as necessary. Be sure to budget for the full cost of the project, including any ongoing maintenance and support costs.

Evaluate the security of the platform.

Security is a crucial aspect of any big data platform, especially if you’re dealing with PII or work in a heavily regulated industry. How will you protect your sensitive data from cyber attacks? You’ll need to ensure that your sensitive data is protected from attacks, breaches, and misuse. This includes making sure that your platform is compliant with relevant regulations, such as HIPAA and PCI-DSS.

Check out our infographic on AI in Cybersecurity to learn ways in which AI is improving cybersecurity.

Look into the integration capabilities of the platform.

You should pick a big data platform that integrates well with your existing systems and tools. This includes being able to easily import and export data, as well as integrating with other platforms such as business intelligence and analytics tools. If you don’t have easy integration it will create a lot of grumpy employees and users.

Consider the scalability of the platform.

It’s important to choose a platform that can grow and adapt as your business needs change. This includes being able to easily add new data sources, as well as being able to scale up or down as needed.

Look for a vendor that offers good customer support and training.

Implementing a big data platform can be complex. Look for a vendor that offers good customer support and training. This will ensure that you have the resources you need to effectively implement and use your new big data platform. Look for a vendor that offers comprehensive documentation, webinars, and training sessions. Additionally, consider whether the vendor offers ongoing maintenance and support, as well as upgrades and bug fixes.

Implementing a big data platform is a big decision that requires careful consideration. By keeping these 10 things in mind, you’ll be well on your way to choosing the right big data platform for your organization. Remember to determine your specific business needs, consider the scale of your data, evaluate your current infrastructure, and consider the cost of both current and future costs. With these factors in mind, you’ll be able to make an informed decision and reap the benefits of big data for your business.

Advance your Skills with CPMAI AI Best Practices

Login Or Register


Register to View Event


Get The 10 things to consider when implementing a big data platform


AI Best Practices

Get the Step By Step Checklist for AI Projects


Login to register for events. Don’t have an account? Just register for an event and an account will be created for you!