A quick guide to Data and Analytics Modernization Shanawaz sheriff June 1, 2022

A quick guide to Data and Analytics Modernization

A hand holding a tablet displaying data and analytics visualization, representing the concept of Data and Analytics Modernization.

Analytics modernization- you must have come across this term one way or another. Data is the most valuable asset in a rapidly digitizing world. Companies are looking to make use of the available data to make error-free, fast decisions, perform better analyses and stay ahead of the customer expectations. Today, every organization prioritizes using data and analytics to stay ahead of the curve. Before we dive into what analytics modernization is, let us take a look at some of the challenges with data analytics.

Data Analytics Challenges and Roadblocks

Industries worldwide are implementing digital technologies to use data as a competitive advantage. However, legacy systems do not provide a flexible and agile analytics ecosystem and lack the capability to handle modern-day data complexities. Some of the analytics challenges that organizations face include:

Exponential data volumes

Today, businesses and consumers are addressing and exchanging data at a much faster pace. Every day, humans create a staggering 2.5 quintillion bytes of data. Often, the high volumes of data pose a challenge for enterprises that do not have adequate tools to perform data analytics at scale and pace.

Data comes in heterogeneous forms

Performing analytics is a challenge for organizations as data comes in varied heterogeneous formats. Integrating data from multiple sources is a challenge for many, with over one-third of organizations citing it as a hassle.

Data is siloed across systems and processes

Legacy systems have data stored in silos across processes and systems, preventing a unified, bird’s eye view. Companies are making a jump from on-prem to cloud and hybrid models to make data accessible and more democratic in nature to perform analytics at scale for better decision-making.

Scarce data talent

Finding a suitable set of individuals who can understand the scope and the right use of your data and analytics can be a hassle. There is a huge skill gap when it comes to leveraging technologies for analytics and making the most out of your data stack.

What is Analytics Modernization?

Data analytics modernization is not just about implementing the newest tools but rethinking the data architecture. Businesses and enterprises adopt modernization frameworks to source relevant data, perform better analysis and understand and deliver what their customers really want.

Analytics modernization is crucial for organizations to make optimum use of the large data volumes that are now available to them. Businesses can seamlessly store, transform, access and analyze data with greater transparency. Storing, activating, and orchestrating different data types is no longer a challenge for organizations that have modernized their data and analytics infrastructures. Modern analytics and IT infrastructure allow the seamless integration of heterogeneous data types -from structured and semi-structured to completely unstructured data sets.

In the digital era, where large volumes of data are harnessed every day, keeping your information secure and scalable is imperative. By migrating your existing analytics environment to the cloud, stakeholders can easily access the information from anywhere. However, that is only half the journey. Finding the right person who will enhance data-driven decision-making is not easy. 87% of organizations face skill shortages after making a move to the cloud. A tech stack partner with deep expertise in data and analytics modernization can be of great help in bridging this skill gap.

Benefits of Modernizing your Analytics Environment

Yes, modernizing your legacy data and analytics environment is a ‘digital transformation’ benchmark. However, intelligent business transformation only occurs when organizations make the proper use of the modernized infrastructure.

Optimizing the full potential of your data is a part of a larger roadmap that aims to achieve long-term business goals. With analytics modernization, businesses and enterprises use the data to predict market behavior and deliver the best business outcomes. That being said, let us take a look at some of the benefits of modernizing your analytics framework:

Rapid data-driven decision-making

In a world connected by digital channels, data is the new currency. Analytics modernization frameworks enable companies to make smart decisions with real-time insights and metrics. Informed decision-making supported with the right data fuels business growth. By discovering the value in data through analytics, keeping up with your customers’ changing behaviors and needs, keeping up with the latest trends and recommending the right products becomes more effortless.

Data source integration and hyper scalability

Being scalable is imperative for surviving in the present-day competitive landscape. Modernized analytics approaches pave the way for data analytics integration platforms, where teams can build scalable infrastructures for short- and long-term business goals. With the right tools, you can automate labor-intensive tasks and shift your focus on growing your enterprise. With data integration, data can be aggregated from any source (internal or external) under a single repository.

Democratize data for shared enterprise knowledge

In order to unlock the true value of your available data, it has to be accessible to all the decision-makers in your value chain. Analytics modernization brings siloed data to a single, unified platform to improve the discovery of crucial data assets. By ‘democratizing’ the data, you make the information available to everyone, both technical and non-technical departments. Companies also need to invest in technologies that enable employees to seamlessly interact with data and make decisions without any dependency.

Now that we have talked about the benefits let’s explore how you can kickstart 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 new norm, leading to even higher volumes of data production. Enterprises have realized that data sitting in disparate silos can be used to leverage and achieve their business goals by modernizing their legacy infrastructures. Listed below are four steps to begin your journey towards becoming a data-driven enterprise:

Get a green light from your CXOs

The analytics modernization journey can only kickstart if the senior leaders are on board. After all, they are the decision-makers. Your first step would be to work with teams that already work with high volumes of data. Identify the individuals or team members whose success rates with data can be used as your use cases. Get a closer view into the data at disparate silos and chart out how modern analytics solutions can help you achieve business goals faster.

Measure the rate of your success

Convincing your stakeholders to invest in analytics modernization requires giving them a clear picture of the ROI. What is your organization going to achieve? What are the business advantages? Identify the various touchpoints of implementing analytics modernization- reduced downtime, increased security, enhanced scalability, data democratization etc. It becomes crucial to sit with senior leaders and discuss the different use cases for modernization that are relevant to your business objectives. Moreover, you need to present an honest scenario; given the constraints of data usage, how far up the ladder would your enterprise grow with the right tools.

Foster a culture of data literacy and data accessibility

A common challenge enterprises face when adopting analytics tools and frameworks is the lack of data literacy. Organizations should prioritize the development of a culture where employees at all levels have access to data sets that make their deliverables and decisions better-informed. Certain people in your organization might have already worked with data. Those who haven’t would face hurdles in understanding the usage and integration of data. Cross-functional teams need to be established where knowledge is shared and data is explored in new ways to unlock new insights and business opportunities.

Identify the data maturity you want to achieve

Every organization has a clear set of goals when they invest in software and technology. Dish out your enterprise objectives and the level of data maturity you’re aiming for. Is centralized data your only objective? What about security and compliance? Are you seeking data portability across edge? Point out the degree to which you see yourself as a data-first organization in the near to mid-term future. Then, map out your long-term enterprise goals and how well they fit within an analytics modernization framework.

Take Full Advantage of your Data with Acuvate

With more and more data becoming available, enterprises demand analytics tools and frameworks to accelerate data-driven business growth.

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