When to Consider Big Data Analytics as a Service
Many businesses have begun using big data analytics as a service, which allows companies to outsource many of their data analysis needs.
As companies gather more data, setting up the right infrastructure and pipeline becomes simultaneously more challenging and more critical. This is especially true when organizations depend on a mixture of structured and unstructured data. Without the right foundation, you can’t leverage the data to effectively generate insights and make informed business decisions.
To solve this problem, many organizations rely on out-of-the-box analytics tools that they place on top of a database. The issue with this approach is that analytics tools rarely prepare the data or perform the custom analysis that answers critical business questions at a granular level. These tools must be paired with data connectors and other solutions, and require a number of technical roles to produce meaningful results: data engineers, data scientists, and analysts, for example.
It’s easy for businesses to lose sight of the big picture as they become mired in the details of particular tools. A partner that offers big data analytics services can ensure that data investments produce beneficial results and that everything runs smoothly, all while providing essential team members.
The team will work to ensure that each piece of the puzzle—from storage to reporting—is where it needs to be and is performing at its peak level. This kind of service also helps put a firm foundation under the whole endeavor; an organization with expertise in these areas can help identify what’s working well and what isn’t, then provide a better understanding of how things should be done.
Here’s when to consider using big data analytics as a service:
To Build the Right Data Infrastructure
It’s not enough for your data to be technically accurate; it should also be accessible and easy to use. Otherwise, you won’t be able to draw meaningful insights from your data or generate a clear and complete picture of your business performance.
This can be accomplished by seamlessly collecting, cleanly storing, and smoothly extracting relevant data from the many systems involved in running your company. To prepare, you might even need to use synthetic data to fill in any gaps in your data pool. However, this is easier said than done!
The process involves many stakeholders with varying degrees of expertise and autonomy. And even if you have the right collection procedures in place, data can quickly become unwieldy if new sources are integrated into the system. This is especially true with no guidance or oversight on handling them so they can feed into your analytics infrastructure.
Under these circumstances, a professional services provider can help you get the most out of your data. By providing independent analysis of your current data sources and procedures, they can objectively assess where you stand in creating an optimal pipeline for your data. In addition, they will help you identify gaps in your current collection processes along with any methods for automating those processes that would optimize efficiency and reduce errors.
To Scale Your Analytics Capabilities
Dashboards and reporting tools used by organizations to aid business teams in data analysis don’t always provide the level of detail required to take action. Many dashboards aree created with a single format in mind and cannot quickly meet all of the requirements of different users and teams.
A manager might, for instance, want to run reports on the effectiveness of each salesperson over the previous year. The manager may wish to allow the sales team access to their individual data while limiting access to information about their coworkers’ performance. In this case, each team member needs specific data access to self-serve their reports.
So it is challenging to scale analytics capabilities to end users. Simply layering an analytics tool like Tableau or PowerBI on top of your database won’t result in the level of granular analysis required for teams to act on the data.
Instead, by creating dashboards specifically tailored to each team’s and end user’s use cases, a services provider can help you scale your analytics capabilities. In addition, a partner can guarantee that the reports and visuals presented to each team or user will benefit their goals by customizing the dashboards for each organization.
A services provider can assist you in scaling your analytics capabilities by designing dashboards and reports unique to each team’s and end user’s use cases, while ensuring the data pipeline supports these critical needs. They can ensure that teams can answer pivotal business questions while maintaining “need to know” access levels for sensitive information.
To Create Custom Machine Learning Algorithms
Data analytics is playing a more critical role in every organization today, but each industry and company will have different analysis needs. A big data analytics provider can help implement custom algorithms that allow for more complex computations tailored to your specific needs.
The difference between standard out-of-the-box analytics and custom algorithms is the ability to move beyond basic metrics like revenue YOY. Businesses are looking to big data to uncover hidden opportunities and solve customer problems.
Custom machine learning algorithms can predict future events or trends based on current data.
They’re used to find patterns in customer behavior or purchases, which can inform business decisions. In addition, advanced statistical models can predict future events, generating actionable insights based on historical purchasing trends.
In the past, if you wanted to perform advanced analyses on your company’s data, you likely would have had to hire a data scientist who could write the code necessary to create custom machine learning algorithms—and that’s just the beginning. As a growing business, you would also need an analytics infrastructure that could store your data and run these algorithms at scale.
Big data analytics as a service offers an alternative to this process by providing all of the components necessary for advanced analytics in one place. In addition, by centralizing your company’s data and processing capabilities, Big Data Analytics as a Service dramatically reduces the time and resources required to implement these algorithms.
Work with a Trusted Data Analytics Services Provider
If you want to build a data infrastructure or scale up your existing infrastructure, Big Data Analytics services are the right choice because they can handle massive amounts of data in real-time and process them quickly. This will give you valuable insights into your business and help you make better decisions.
Big Data Analytics Services can also be used to create custom machine learning algorithms—a unique way of teaching computers how to learn from data independently rather than being programmed by humans. Although machine learning already exists, custom algorithms give businesses an edge over others of the same kind because they are more tailored.
We work with all sorts of companies who use this technology and can help you incorporate it into your business model. When you need big data analytics capabilities that your in-house team doesn’t have, you can look to a company like KMS for assistance. Schedule a free consultation to discuss your technology needs.
Understanding and implementing Big Data Analytics as a Service can greatly benefit your organization, but combining this with efficient DevOps practices can take your software development and deployment to the next level. To learn more about how DevOps can streamline your development processes and enhance your software capabilities, check out our DevOps blog category. Find articles on building effective DevOps teams, overcoming common DevOps challenges, and leveraging DevOps for optimal results in your projects.
