In a data-driven business world, real-time insights are valuable for enterprises but challenging to acquire in a scattered data environment. Enterprise customers need a data lakehouse platform that can unify this distributed data and deliver real-time analytics.
But first, what are real-time insights and why are they growing in importance?
Simply defined, real-time insights are the instantaneous output of actionable information after data processing and analysis, as it's being generated or received. For instance, Telecom companies can utilize real-time data insights to track the use of their provided services and the quality of the connection. Similarly, the hospitality sector can use real-time insights to determine accommodation costs (based on the current demand).
That said, enterprises do face a host of challenges with acquiring and scaling real-time insights. Here are some of them:
- Data volumes
With over 402 million terabytes of data created each day, it’s common to find legacy data systems struggling to cope with the massive influx of data.
What makes it more challenging is that enterprises receive or generate data from a variety of sources and at high velocities. This makes it difficult for enterprises to generate real-time analytics. They need a modern system with parallel processing capabilities. This enables enterprises to manage massive data streams by distributing their computations across a network of clusters. - Data latency
Real-time data analysis also depends on the speed of extracting insights. High latency can directly impact the response time, thus hindering enterprises from responding immediately to real-world events or sudden changes in customer behavior.
Enterprises can reduce data latency and facilitate faster analysis by using techniques like in-memory computing and caching. Besides, through advanced data visualization, decision-makers can quickly identify data patterns and trends – thus minimizing the business impact of high latency. - Low-quality data
Data quality and accuracy are crucial for extracting real-time insights. With inconsistent or missing data, enterprises often generate error-prone insights, which can lead to misinformed decisions. Thus, they must maintain data integrity during the analytical process.
For accurate insights, enterprises must ensure proper data ingestion and processing with the following quality controls:
- Data validation checks
- Data quality monitoring
- Schema enforcements
With data integration across multiple sources, enterprises can prevent any data loss – and ensure a continuous and consistent flow of real-time data.
- Limited scalability
Traditional systems are not built to scale according to rising data volumes and complexity. Additionally, as data sources keep on multiplying, traditional systems
cannot keep pace with the growing demands for real-time insights.
Enterprises can improve their scalability by switching to a cloud infrastructure, which ensures optimum performance even during peak demand. They can also leverage their cloud resources to scale up their data processing capabilities. Besides cloud solutions, a container-driven infrastructure can dynamically scale resources according to real-time demand. - Lack of predictive insights
To maximize the business outcome, enterprises need real-time insights that can predict future trends and developments. For example, business intelligence (BI)
provides a competitive advantage when powered by real-time data insights.
Traditional systems simply lack predictive analysis capabilities, which can impact BI and decision-making skills. To address this challenge, enterprises need an AI-
powered demand forecasting system with embedded predictive models. This enables them to stay ahead even in dynamic market conditions and fluctuations.
How MS Fabric Lakehouse can help in real-time insights
Integrated with the MS Azure cloud platform, MS Fabric Lakehouse is essentially a comprehensive data analytics platform that can deliver real-time insights, thus
transforming business intelligence.
As a modern data lakehouse, MS Fabric integrates the best capabilities of both data lakes and warehouses. This includes the structured data storage of a warehouse and the in-built scalability of a data lake. Here’s how this tool can overcome the challenges associated with real-time insights:
- Unified data
With its shared architecture, MS Fabric provides a unified data stack, which enables an integrated environment – comprising components from Power BI, Azure Synapse, and Data Factory. - Real-time analytics
The cloud-powered MS Fabric platform provides real-time analytics through its big data analytics platform. Using performance-based querying language, MS Fabric enables enterprises to search through structured, unstructured, and semi- structured data sources. - Data ingestion
With its OneLake lakehouse storage layer, MS Fabric enables real-time data ingestion from multiple sources including:
- Azure-based data services
- On-premises databases
- External cloud storage platforms like Amazon S3
Effectively, MS Fabric provides data ingestion, processing, and analysis within the same unified platform – thus enabling real-time access to both structured and unstructured data at all times.
- AI capabilities
As part of the MS Azure suite, MS Fabric can leverage the AI capabilities of Azure like Azure Cognitive services and Azure machine learning. Effectively, MS Fabric can integrate AI tools for predictive modeling and data visualization.
Additionally, MS Fabric can improve real-time data analytics by using AI models and conversational language processing. It can incorporate AI-powered innovations like Copilot and ChatGPT to extract fresh data insights.
Conclusion
Scattered data sources along with high operational costs can disrupt any enterprise from acquiring real-time insights to drive their decision-making process. With its unified data architecture, MS Fabric Lakehouse is the right solution to enabling real-time analytics and cost efficiency.
As a leading partner for MS Azure, Parkar Digital can help you unlock data potential with its Data and Analytics service – and power your business innovation with its AI services. Here’s a glimpse of how we enabled one of our enterprise customers to improve their real-time data insights using MS Fabric Lakehouse. Here are some of the results:
- 35% faster data processing
- Annual savings of $500,000
Ready to leverage the power of real-time insights and analytics. Contact our team today.
