Success Factors Of Having A Robust Data Platform For A Modern Enterprise

Introduction

In today's data-driven world, we see businesses overwhelmed with the sheer volume and variety of data. To make sense from this exponentially growing data, organizations rely on traditional data management systems, which results in slower growth, higher inefficiencies, and inability to keep up with competition. We know data has become a driving force which needs to be unlocked to extract its true value and turn it into a competitive advantage. Well, Data Platform Modernization holds the key. To truly succeed in the digital age, businesses need to have a robust Modern Data Platform in place, which leverages the right technologies to manage data. Read on to discover why data modernization is no longer an option, but a necessity for staying ahead in today's data-driven world.

 

What is Data Platform Modernization?

Data Platform Modernization involves updating and transforming traditional data management systems by adopting new technologies. In today’s time it is a natural response to accommodate the rapidly increasing volume and complexity of data generated from various sources. Data modernization helps enterprises process and analyse large amounts of data faster, extract valuable insights, and make informed decisions, thus increasing efficiency, reducing costs, and ensuring data security and privacy.

Challenges in Managing Modern Enterprise Data

The better an organization manages its data, the more profound impact it will witness. But the sheer volume of data from ever-evolving sources increases the complexity in effectively integrating data and implementing data governance and security. Let’s dive a little deeper to understand these challenges: 

1. Measuring Outcome

“You can’t manage what you don’t measure.”

As the management guru Peter Drucker famously said, “If you can't measure it, you can't manage it.” You need to constantly measure and track your organization’s performance to stay up to date and make proactive decisions.
Due to large data volumes generated from multiple sources, it’s becoming increasingly difficult for enterprises to determine the impact of data on operations.  The challenge lies in capturing the right data, analysing it, and presenting it in a way that provides meaningful insights. This requires not just technology, but also the right data management processes, skilled personnel, and the ability to identify key performance indicators (KPIs) that align with the organization's goals. Without the ability to measure outcomes, an enterprise's data investment may not yield the desired results, leading to missed opportunities and unfulfilled potential.

2. Data Volume

The volume of data created, replicated, stored, and accessed across enterprises is ever-increasing, especially when organizations are scaling up. 

Data is generated by multiple sources including internal systems, IoT devices, cloud applications, and social media.  The volume of data generated is so massive that it becomes difficult to store, process, and analyse it effectively, leading to challenges like: 

Questionable data availability and reliability 
Complexities in processing data to generate actionable insights
Difficulty in implementing proper data governance 
Inability of data to meet the required SLAs

Challenges associated with data volume can be addressed by leveraging the latest tools and technologies that can equip organizations to utilize their data assets and make the most out of them.

3. Data Management

Modern enterprises face several challenges in data management, including disparate data sources, poor data quality, lack of security and governance, and rapid technology adoption leading to data silos. These challenges can have consequences, including inconsistent and outdated data, poor data quality leading to incorrect analysis and decision-making, data breaches and theft, lost opportunities due to data silos, and regulatory challenges due to lack of governance. An enterprise must have a comprehensive data platform modernization strategy that addresses the technical, operational, and governance aspects of data management. This strategy should include data integration practices to ensure the consistency, accuracy, and timeliness of data across the organization, along with data quality improvement through the implementation of data profiling, cleansing, enrichment, and standardization processes. The new data platform must also be easy-to-use such that with some training, employees can enhance their ability to effectively manage and leverage data.

By addressing these technical challenges, modern enterprises can effectively manage their data, protect sensitive information, and leverage data to drive business success.

4. Data Integration

Enterprises need a seamless integration framework to ingest data from multiple sources into a centralized repository. However, the integration of data from different sources is becoming increasingly complex due to differences in data structures, formats, and protocols.

A critical challenge is to identify to what extent the existing data platform is capable of data ingestion from multiple sources. A hybrid model consisting of on-premise or legacy systems can get complex especially due to certain types of data e.g. social media data and connected devices. Cloud solutions area one step ahead and are capable of ingesting data from multiple sources. Moreover, a modern solution should be able to integrate data from different sources quickly and efficiently, handle diverse data types, and provide a comprehensive view of the data.

5. High Maintenance Cost

For most organizations, data is stored in both structured and unstructured form, and it’s the responsibility of the IT department to manage it. Managing the data can be challenging especially for growing organizations, which need to invest more time and resources to handle increasing volumes of data efficiently.

The high volume of data makes it difficult and expensive to extract,  transform, and load the data. The high cost of maintaining data hardware and ecosystems, whether on-premise or legacy infrastructure, can be a major hurdle in evolving organizations’ data transformation journey for many organizations.  

6. System Outage 

System outage during peak season due to high load of data is another challenge. This concern increases the need to manage and monitor the performance of the system. It has become imperative for organizations to keep track of the system’s performance and ensure it is running smoothly. Having a robust monitoring system is key to ensure zero system errors and failures.

Why is it Important to Have a Solid Data Foundation in an Enterprise

In today's fast-paced and data-driven business world, a robust data platform is crucial for driving growth and staying ahead of the competition. Without the ability to turn data into actionable insights, data can become more of a liability than an asset. To achieve fast, efficient decision-making and remain competitive, organizations must modernize their data platforms to make them more agile and effective. Investing in the right tools to process data and extract valuable insights from it is essential for sustained success in the long run.
But oftentimes data platforms are running on outdated, inefficient technologies, making it difficult for organizations to unlock the value of their data. Additionally, relying on a legacy system slows down the value that the data can bring.

Let’s look at the top reasons why data modernization matters:

Cost Efficient

Enterprises need an affordable solution to execute diverse business use cases that would otherwise be costly with their on-premises or legacy infrastructure. These infrastructures are subject to increasing maintenance and security costs. Data modernization is an essential piece of the puzzle when it comes to these business initiatives. It helps to solve the problem of legacy data management systems and the costs associated with it, in turn increasing the value of your data.

Improves Performance 

Data platform modernization enhances performance through improved scalability, faster data processing, increased data availability, enhanced data management, better data analysis, and improved data integration.  It allows enterprises to store and analyse data more efficiently. Additionally, modern data platforms provide advanced analytics capabilities, including real-time analytics and machine learning, thereby enabling organizations to make data-driven decisions faster and more accurately,  to achieve business growth.

Business Continuity

Having a strong data foundation framework is essential for the advancement of the data maturity model in the enterprise. The data foundation framework provides a solid premise that will allow enterprises to successfully scale and reach their desired level of data maturity. Modern Data Platform ensures a more reliable, secure, and resilient infrastructure for data storage and processing, which in turn helps enterprises minimize downtime, protect against data breaches, and ensure the availability and integrity of their data, even in the event of a failure. 

Unified View of Your Data

Strategic data analytics helps to identify trends and patterns in data that can be used to inform decision-making. Having a standard and a unified view of data, which is made possible with data modernization, makes it easy to access, use and understand the data. This is essential for streamlining operational processes and improving digital experiences. 

Conclusion 

IT modernization is crucial for businesses to survive in today's rapidly changing market. A modern data platform enables data to be integrated, analysed, extracted, and finally delivered to the relevant stakeholders in the form of reports, dashboards, and insights in a secure & useful way. It gives companies a competitive advantage due to its robustness, agility, and ability to enable advanced analytics.

The recent pandemic crisis exposed many businesses that were held back by their outdated legacy systems. Relying on old and outdated systems limited their ability to adapt to changing market conditions and hindered their growth. The results from a McKinsey survey suggests that for most companies, the need to work and interact with customers remotely requires investments in data security and an accelerated migration to the cloud. With this trend, there has been a surge in the need for a centralized data storage system like the cloud over individual or on-premise storage systems.  

Moving your data to the cloud makes data accessible across and outside the business and ensures compliance with data security and privacy regulations. Modernizing your data platform is essential and ready for cloud and will ultimately help you to stay relevant and ensure your business is ready for scale and disruption.