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‘Data is the new oil’ or ‘Data is the new gold’ were the headlines that we saw very often recently. Today, companies across industries from FMCG to Finance are sitting on mountains of data (that double every two years). Yet the vast majority are only able to leverage a fraction of its potential. McKinsey study reveals that most companies utilize a mere 3-5% of the data they possess. The reasons for this include siloed data ecosystems, redundancy in tools and a lack of unified data quality strategies. Imagine what would happen if companies could use for example 20-30% of their data instead of only 3-5%. Such a leap could revolutionize their business and decisions. This article will explore data challenges and share insights on how modern data technology can address them. 


The Data Challenges 

Siloed Data Ecosystems: A Barrier to Insight 

One of the foundational problems in leveraging big data is the existence of siloed data ecosystems. Data scattered across various systems, each with its own technology, format and architecture, makes it very difficult to achieve a unified view. And a unified view is essential for key business decisions. This fragmentation is often magnified by the redundancy of tools and applications (legacy). A byproduct of continuous, but uncoordinated technical transformations, each addressing isolated business use cases. 
It comes with no surprise that in recent Forrester study, 80% of managers say reducing silos are a top priority for their organization. 


The Quest for Quality and Performance 

Another significant challenge is maintaining the quality of data. Without a cohesive strategy to ensure data integrity, businesses struggle to rely on it for critical decision-making. Wrong data leads to wrong decisions. The consequences are significant – Forrester reports that 67% of data remains unanalyzed, with a staggering 95% of companies unable to analyze unstructured data. This untapped data is a lost opportunity for deriving actionable insights. Compounding this issue is the exponential growth in data volume, with global data expected to increase by 40% annually (Science Direct). This growth puts immense pressure on existing data management systems, highlighting the need for scalable and efficient solutions. 


Leveraging Technology: The Path Forward 

Flexible Architecture and Tailored Solutions 

The evolution of technology, particularly the adoption of microservices, offers a glimmer of hope. Microservices provide the flexibility to design tailored solutions that can adapt to specific business needs, covering all aspects of the data lifecycle. This approach ensures integrity and compatibility among services, allowing for the integration of new functionalities as business needs evolve. It also secures future scalability of data architecture. 


Enhancing Data Quality and Accessibility 

Technological advancements in data ingestion and quality management, such as plug-and-play solutions, enable businesses to cleanse, normalize and standardize their data in real time. Such advancements not only improve the reliability of data but also pave the way for the creation of Single Object View – crucial for entities like consumers and products. The key example is Single Consumer View. This is a unified profile, consolidating information from all sources into a comprehensive ‘Golden Record’ – a vital asset for any business that deals directly with consumers. 

Moreover, the ability to integrate various data models through multiparadigm storage or data virtualization enables Single Consumer View across diverse data models, without costly data migrations or transformation of the whole ecosystem. 


Leveraging High-Performance Tools 

To navigate the complex data maze, businesses require tools that can handle high-volume datasets with speed and efficiency. Additionally, low-code frameworks for custom data tools enable smooth integration with external data visualization like PowerBI or Tableau, further increasing the usability of data. Such environment not only speeds up the decision-making process but also makes working with data much more user-friendly. 

The Road Ahead 

The journey towards becoming a data-driven organization requires not just the right technology but a strategic approach to data management that emphasizes flexibility, scalability, and quality. As businesses look to unlock the full potential of their data, the lessons learned from pioneering solutions and real-world applications provide a roadmap for overcoming the challenges of big data. 

By adopting a holistic view of the data lifecycle and investing in technology that addresses the core issues of siloed systems, data quality, and scalability, companies can transform their data into a strategic asset that drives decision-making and competitive advantage. 


Conclusion: Turning Data Into a Strategic Asset 

The path through the data maze is fraught with challenges, but with the right technology, businesses can navigate it successfully. Transforming data from a byproduct of business operations to the foundational pillar for strategic decisions. The future of data management lies in leveraging flexible, scalable technology that not only addresses current needs, but evolves with us towards the future.