A quick guide to Data and Analytics Modernization

Analytics modernization – you must have come across this term in some way. In a rapidly digitizing world, data is the most valuable asset. Companies want to use available data to make error-free, timely decisions, perform better analyses, and stay ahead of customer expectations. To stay ahead of the competition, every organization prioritizes data and analytics. Let’s look at some of the challenges with data analytics before we get into what analytics modernization is.

Data Analytics Challenges and Roadblocks

Industries worldwide are implementing digital technologies to gain a competitive advantage through data. Legacy systems, on the other hand, do not provide a flexible and agile analytics ecosystem and are incapable of handling modern-day data complexities. Organizations face the following analytics challenges:

Exponential data volumes

Businesses and consumers are addressing and exchanging data at a much faster rate these days. Every day, humans generate 2.5 quintillion bytes of data. High volumes of data are frequently a challenge for enterprises that lack adequate tools to perform data analytics at scale and pace.

Data comes in heterogeneous forms

Analytics is difficult for organizations to perform because data comes in a variety of heterogeneous formats. Integrating data from multiple sources is a challenge for many organizations, with more than one-third citing it as a hassle.

Data is siloed across systems and processes.

Data is stored in silos across processes and systems in legacy systems, preventing a unified, bird’s-eye view. Companies are shifting from on-premises to cloud and hybrid models to make data more accessible and democratic to perform analytics at scale for better decision-making.

Scarce data talent

Finding the right people to understand the scope and proper application of your data and analytics can be difficult. When it comes to leveraging technologies for analytics and making the most of your data stack, there is a significant skill gap.

What is Analytics Modernization?

Data analytics modernization entails implementing the most recent tools and rethinking the data architecture. Businesses and enterprises use modernization frameworks to gather relevant data, conduct better analysis, and understand and deliver what their customers truly want.

Analytics modernization is critical for organizations to use the massive amounts of data now available. Businesses can store, transform, access, and analyze data more transparently. For organizations that have modernized their data and analytics infrastructures, keeping, activating, and orchestrating various data types is no longer challenging. Modern analytics and IT infrastructure enable the seamless integration of disparate data types, ranging from structured and semi-structured to completely unstructured.

Keeping your data secure and scalable is critical in the digital age, where massive amounts of data are collected daily. Stakeholders can easily access information from anywhere by migrating their existing analytics environment to the cloud. However, this is only half of the story. Finding the right person to improve data-driven decision-making is difficult. After migrating to the cloud, 87% of organizations face a skills shortage. A tech stack partner with deep data and analytics modernization expertise can be highly beneficial in closing this skill gap.

Read more: What is Advanced Analytics?

Advantages of Modernizing your Analytics Environment

Modernizing your legacy data and analytics environment is a ‘digital transformation’ benchmark. On the other hand, intelligent business transformation occurs only when organizations properly use modernized infrastructure.

Optimizing the full potential of your data is part of a larger strategy to achieve long-term business objectives. With analytics modernization, businesses and enterprises use data to predict market behavior and deliver the best business outcomes. That being said, here are some of the advantages of modernizing your analytics framework:

Rapid decision-making based on data

Data is the new currency in a world linked by digital channels. Analytics modernization frameworks enable businesses to make better decisions by providing real-time insights and metrics. Informed decision-making supported by relevant data drives business growth. Discovering the value in data through analytics makes keeping up with your customers’ changing behaviors. It needs easier to stay up to date on the latest trends and recommend the right products.

Data source integration and hyper scalability

Being scalable is critical for surviving in today’s competitive landscape. Modernized analytics approaches pave the way for data analytics integration platforms on which teams can build scalable infrastructures for both short- and long-term business objectives. With the right tools, you can automate time-consuming tasks and focus on growing your business. Data integration allows data to be aggregated from any source (internal or external) and stored in a single repository.

Democratize data for shared enterprise knowledge

It must be available to all decision-makers in your value chain to realize the actual value of your available data. Analytics modernization consolidates disparate data sources into a single, unified platform to improve the discovery of critical data assets. By ‘democratizing’ the data, you make it available to all departments, both technical and non-technical. Companies must also invest in technologies that allow employees to interact with data in real-time and make independent decisions.

Now that we’ve covered the advantages, let’s look at how you can start your analytics modernization journey.

4 Steps to Begin your Analytics Modernization Roadmap

Covid-19 challenged and changed the traditional notions of work. Remote working and customer engagements have become the norm, resulting in higher data production volumes. By modernizing their legacy infrastructures, enterprises have realized that data sitting in disparate silos can be leveraged and used to achieve business goals. Here are four steps to get started on your path to becoming a data-driven enterprise:

Get a green light from your CXOs

The journey toward analytics modernization can only begin if senior leaders are on board. After all, they are the ones who make the decisions. Your first step should be collaborating with teams already dealing with large amounts of data. Identify individuals or team members whose data success rates can be used as use cases. Examine the data in disparate silos and map how modern analytics solutions can help you achieve business goals more quickly.

Measure the rate of your success

To persuade your stakeholders to invest in analytics modernization, you must first demonstrate the ROI. What is your organization going to achieve? What are the business benefits? Determine the various touchpoints of implementing analytics modernization, such as reduced downtime, increased security, increased scalability, data democratization, and so on. Meeting with senior leaders and discussing the various modernization use cases relevant to your business objectives is critical. Furthermore, you must present an honest scenario: how far up the ladder would your enterprise grow with the right tools, given the constraints of data usage?

Foster a culture of data literacy and data accessibility

A common issue businesses face when implementing analytics tools and frameworks is a lack of data literacy. Organizations should prioritize the development of a culture in which employees at all levels have access to data sets that improve the quality of their deliverables and decisions. Specific individuals in your organization may have previously worked with data. Those who haven’t will have difficulty understanding data usage and integration. To uncover new insights and business opportunities, cross-functional teams must be formed in which knowledge is shared and data is explored in novel ways.

Determine the data maturity you want to achieve

When an organization invests in software and technology, it has specific goals. Describe your enterprise goals and the level of data maturity you want to achieve. Is centralized data your only goal? What about safety and security? Are you looking for data portability across the edge? Indicate how far you see yourself as a data-first organization in the near to mid-term future. Then, sketch your long-term enterprise goals and how they relate to an analytics modernization framework.

Take Full Advantage of your Data with Bestarion

As more data becomes available, businesses require analytics tools and frameworks to accelerate data-driven business growth.

However, without the right tools and knowledge, making sense of your data and using it to your competitive advantage can be complex and perplexing. Bestarion enables you to move past data as a spinoff and derive maximum value from your analytics environment for enterprise success. With Bestarion, you can unlock the full potential of your data and analytics capabilities and turn them into your competitive advantage.