According to a study, the global analytics on cloud market was valued at $22.07 billion in 2021 and is expected to grow at a CAGR of 22.32% up until 2030. Much of this growth can be attributed to the growing cloud adoption.
With the cloud, enterprises are looking to accommodate the escalating data volumes, address the challenges posed by the legacy on-premises infrastructure, and alleviate data silos and departmental fragmentation. It's here that cloud analytics becomes a viable approach. However, moving analytics to the cloud isn't without its challenges.
First Off, Why Move Analytics to the Cloud?
Analytics on the cloud offers a range of benefits, including:
- SaaS-based delivery, so data scientists and engineers can spend their time evaluating patterns rather than underlying infrastructure management
- Scalability across various workloads and high availability with built-in redundancies
- Robust data backup and recovery mechanisms, safeguarding the data against unexpected incidents or disasters
- High accessibility from anywhere, facilitating collaboration among teams regardless of their physical location
- Democratization of insights and the heightened involvement of business users
- Cost-effective access to knowledge hidden in the enterprise data
Top 5 Challenges of Moving Analytics to the Cloud
Despite the undeniable benefits of moving analytics to the cloud, there are many barriers and challenges to overcome. We've put together a list of the top five challenges that businesses face when moving analytics to the cloud:
- Data Security and Governance
Protecting data has never been more important. As per IBM’s 2023 report, the average cost of a data breach in 2023 is $4.45 million and almost 51% of organizations and investing in security solutions like incident response planning, threat detection, etc., to curb the threat.
With the amount of information we create, store, and manage, we must ensure data is protected from unauthorized use and access. The key is properly securing the data and then sharing it per governance policies and processes, ensuring compliance with regulations such as GDPR (General Data Protection Regulation) and CCPA (California Consumer Privacy Act). This ensures the data is sent securely and not to unauthorized parties.
There's also the need to adequately configure settings in the cloud control panel; otherwise, the data at the disposal might get exposed. Apart from that, organizations can struggle from not having a lot of control over their data and being reliant on cloud vendors for all the security mechanisms.
- Integration and Data Migration
Integrating data from various sources and migrating it to the cloud can be complex and time-consuming. Data is often stored in different formats, so you have to spend a lot of time converting the data. Data can also come from many different sources, which makes aggregation challenging.
At the end of the day, it's the organizations' responsibility to ensure that their data is up-to-date and consistent. They must have a robust strategy in place for effective data migration.
The process becomes easier when the migration is carried out per a concrete strategy. Whether there are multiple data sources, custom business rules, or manual joins between source systems, once you're in the cloud, you have access to a great deal of functionality, such as programmable interfaces and quick processing speed.
- Cost Management
Although the pay-as-you-go model is exceptionally viable in lowering the cost-related entry barrier to effective analytics operations, organizations must be cognizant of the fact that these costs can escalate quite quickly if they aren't keeping track of the functions utilized and the costs they accrue.
In fact, Flexera’s 2023 State of the Cloud Report reveals that 82% of the organizations regard “managing cloud spend” as the biggest challenge. Security (79%), lack of resources (78%), and governance (71%) follow suit as the other top cloud challenges.
That said, organizations need to be cautious about potential cost overruns. Several factors can influence the cost and performance of cloud analytics initiatives, including the type/functionality, subscription duration, provider, region/country, etc.
- Skills and Talent Gap
In 2020, a McKinsey survey outlined that 43% of the respondents were already experiencing skill gaps. About 22% outlined that they would be in this situation in the next two years, while 22% believed that they'd face skill gaps in the next 3-5 years. Throughout this survey, data analytics was found to be the area with the greatest skills gap.
As it stands, analytics on the cloud also requires specialized skills and expertise, which may not be readily available within an organization. As data volume increases, the ability to perform analytical processing in real-time becomes a requirement. Closing the skills gap and training existing employees or hiring new talent with cloud analytics proficiency can be a significant hurdle.
- Driving Value Creation
Once an organization has managed to overcome the above-mentioned challenges, it must still make sure that it's getting the most out of its cloud analytics initiative. It's imperative that organizations are able to derive real and meaningful insights from their data.
In its 2022 report, McKinsey revealed how developing data analytics models is still challenging for data scientists owing to problems like data duplication, sprawling, siloed environments, etc.
So, it's exceptionally critical that organizations overcome such challenges and those associated with half-baked data sets, over-engineering, and lack of business context. They must also train their analysts and business leaders on how to make the most of analytics programs on the cloud and how to progress through the different business intelligence (BI) maturity levels.
How Working with an Experienced Partner Can Help Address These Challenges
With so many moving parts, providers, modalities, and use cases to consider, it's no surprise that many CIOs struggle to identify the best approach to kick-start their cloud-based analytics journey. However, they must overcome the hurdles to realize the benefits of cloud analytics.
Favorably, collaborating with an experienced technology partner can appreciably enhance the enterprise's success in the realm of cloud analytics. An established partner can help:
- Provide key insights and expert guidance on navigating complex cloud analytics challenges
- Facilitate strategic tools and technologies selection per the business needs
- Streamline the process of data migration and setting up the cloud analytics infrastructure
- Navigate cost structures effectively to ensure maximum value from cloud investments
- Drive innovation and enhance analytics capabilities for sustainable growth
Surely, the benefits of transitioning analytics to the cloud, including streamlined resource management, performance, scalability, etc., are compelling. Yet, demanding situations, as outlined above, persist. Navigating these hurdles efficiently requires expert guidance. This is precisely where Recode can help. Contact us to learn more about how we can help you successfully move analytics to the cloud.
