Top 7 Challenges of Moving Data Analytics to the Cloud

Moving data analytics to the cloud would be much simpler if it were a “lift and shift” process. A lift and shift to the cloud involves moving applications and associated data to the cloud without redesigning the applications. Since that’s not possible when you’re moving analytics to the cloud, you need to be prepared for the challenges you’ll face.

 
However, those challenges shouldn’t discourage you. Running data analytics in the cloud is a necessary step in being able to get faster insights, make better decisions, innovate more effectively, increase agility, and achieve a stronger competitive edge. Here are the top seven challenges you’ll need to consider.

1. Technology Infrastructure

   This is one of the technology areas that is changing constantly. If you look at what’s out there today and compare it to what’s available in six months, you’ll find many changes. Right now, Snowflake and Amazon Redshift are the two hottest database technologies. But, there are many players in the data analytics market. You’ll need to find solutions that will be strong over the long term, and that work well together to meet your needs.

 

2. Governance and Risk Issues

   Virtually every company has governance issues they need to address. Personally identifiable information (PII) may end up in your cloud and you’ll need to comply with regulations that affect your industry in terms of protecting it. If you’re in or related to the healthcare industry, for example, you need to be concerned about complying with the Health Insurance Portability and Accountability Act (HIPAA). You’ll need to determine how you can set up protections such as masking PII and HIPAA data or encrypting it.

   Cybersecurity is a big issue for every business, given the fact that cybercriminals are active in almost every industry. All of the data you use for analytics needs to be protected against cyberattacks.

 

3. Adding More Flexibility to the Data

   The way your data and analytics systems are currently functioning will probably not provide the level of flexibility and agility that your customers will want when they have access to those systems in the cloud. You’ll need to plan ways to make those systems more flexible to meet your organization’s requirements over time.

 

4. Integrating Multiple Data Sources

   Any application that needs to consolidate data from multiple sources presents a problem whether you’re working on-premises or in the cloud. You may need a master data management strategy to ensure that your product, customer, service, and supply data are consistent. If a customer is shown as L. S. Associates in one database and LS Associates in another, you’ve got a problem. You’ll need to be able to create a solid foundation with the data in order to leverage the analytics on top of it.

 

5. Acquiring New Skills and Capabilities

   Moving your data analytics to the cloud means that you’ll be using new technologies. You may choose to use Snowflake or Amazon Redshift, and you may review additional AWS or Microsoft technologies. You’ll need to determine if you have the skills in-house, or if they’re available in the market, to let you use the new technologies effectively. If you don’t have those skills and capabilities available now, you’ll need to develop a plan to obtain them either through internal training or outside hiring.

 

6. Making Data More Usable

   Data analytics isn’t about just the technology. It needs to be driven from within the business. You’ll have customers asking questions such as, “How can I become more innovative and efficient—how can I help the business grow?” You’ll need to determine how to structure the data to answer those types of questions.

 

7. Guiding Your Organization Through the BI Maturity Stages

   The questions you’ll need to answer will depend on where your organization is in terms of Business Intelligence (BI) maturity. In general, your organization will move through five stages of maturity and will need different tools at each stage:
    

   • Running the business: Reports that show what happened in the business.
   • Measuring and monitoring the business: Reports that help measure performance and monitor what is happening in the business.
   • Integrating performance management and the business: Reports that measure KPIs across the organization and give insight that will help the organization respond to what’s happening.
   • Fostering innovation and people productivity: Using the cloud to deploy enterprise metrics and actively researching new methods and technologies.
   • Creating market agility and differentiation: Using the cloud capabilities to drive innovation, define business strategies, and achieve transformation within the business.

    
   You’ll be challenged to understand where your organization is in terms of BI maturity and put tools and processes together that will help the organization move things forward. In the later stages, you’ll need to leverage artificial intelligence, machine learning, and more.

Datavail is working with a number of clients to address their data analytics needs, spanning different sizes and industries. Our expert team can help you ensure that you develop the type of innovative and agile capabilities that will bring your business into the future successfully.

For more information, download our white paper, A Panoramic View of Cloud Analytics: The Insight You Need to Grow Your Business. Or, contact a Datavail analytics expert to find out how we can help you with your cloud analytics and business intelligence initiatives.