Why Modern Enterprises Need Real-Time Analytics

In a fast-paced world, users need insights in real-time as data enters the system to make informed decisions and respond to events. The data needs to be prepared and measured when it enters the database for processing. Real-time analytics enables businesses to leverage opportunities without delay or proactively prevent problems before their occurrence.

There are many use cases for real-time analytics in modern enterprises. For instance, financial institutions can extend credits based on real-time credit scoring. Businesses can service customers better by providing personalized incentives and discounts based on insights obtained from data about their preferences and past purchases. Frauds can be detected at points of sale.

To know more about Indium’s Striim and real-time analytics capabilities, click here

Get in touch

Advantages of Real-Time Analytics

In traditional batch analytics, there is a lag between receiving data and drawing the insights. This can make it hard to respond appropriately since there is a constant change, and what was relevant a day ago may be nothing today. With real-time analytics, businesses can improve the quality and speed of decision-making, identify gaps and strengths on the go, and improve their operational efficiency. Some of the benefits of real-time analytics include:

  • Customer Profiling: Businesses can analyze customer data in real-time to understand their preferences and personalize offers and campaigns to serve them better. This can help with cross-selling and upselling as well.
  • Cost Efficiency: Real-time analytics can help identify areas of improvement, enabling resource optimization to save costs and enhance efficiency.
  • Quicker Response: Every day is new in today’s world with fluctuations in the market, political upheavals, climatic changes, changing market trends, and so on, impacting the business. With real-time analytics, companies can ensure that they respond appropriately to leverage the situation or invest cautiously.
  • Make Business Agile: Along with speed, it also empowers business users to improve the quality of their decisions and make the business more agile and responsive. It helps with choosing between different possible courses that align with business goals and strategies.
  • Improve Operational Efficiency: Businesses can identify bottlenecks and gaps to improve operations. In manufacturing industries, real-time analytics can help with predictive maintenance to reduce downtime and unplanned disruptions. Logistics companies can improve the efficiency of delivery by identifying better routes, incentivizing drivers who perform to increase their efficiency, use predictive maintenance to keep their vehicles in good condition, and so on. 

Challenges in Real-Time Analytics

While real-time analytics promises much, it also requires applications that are highly available and respond quickly to be effective and deliver. They should be able to handle large volumes of data, even up to terabytes, and respond to queries within seconds.

Some other factors to consider include changes to data sources, the need for scalable data storage, a data archiving strategy, and provision for a backup in case of system outages or other issues.

Striim – A Modern Real-Time Analytics Solution for the Modern Enterprise

Striim Platform helps businesses adopt a modern data architecture that allows quick ingestion, processing, and delivery of real-time data across diverse environments in the cloud or on-premise.

It is a unified platform that provides an end-to-end solution for the entire analytics process from real-time data ingestion to stream processing, pipeline monitoring, and real-time delivery with validation. It can ingest a wide variety and large volumes of data from databases, both enterprise (Oracle, SAP)and non-enterprise variety (PostGres, MySQL), using low-impact change data capture (CDC), log files, Hadoop, messaging systems, cloud applications, and IoT devices at high speeds in real-time.

One of the key features is in-flight data processing that filters, transforms, aggregates, masks, and enriches streaming data with reference data prior to delivering to diverse environments such as the cloud or on-premise with sub-second latency. It has in-built pipeline monitoring and validation capabilities that enable tracing and confirming that streaming data has been ingested, processed, and delivered.

You might be interested in: Multi-Cloud Data Pipelines with Striim for Real-Time Data Streaming

Striim Real-Time Analytics Features

Some of its features include:

Connecting to Data: Striim provides wizards for the real-time integration of data to build data flows using templates that are searchable. Using the wizard, you can connect to the data source, which will be verified to ensure the correct configuration. When connecting with a CDC source, the verification will cover permissions and whether the database set up supports CDC.

Building Data Flows: Data flows can be built from scratch by defining the process for collecting, processing, and delivering data.

Monitoring: Once the data flow application has been built, running data will be ingested continually from the sources, followed by real-time processing and delivery to the targets with very low latency. The state of data flows is made possible in real-time using monitoring that helps with the easy identification of any bottlenecks.

Validation: Striim also validates the delivery and reveals any lag end-to-end transparently. Such visibility helps with mission-critical systems that require SLAs for ensuring that the data is current. Further, drilling down any of the components in a data flow enables detailed statistics such as read/write rate, latency, CPU usage, lag, and other metrics. This will help with identifying bottlenecks and tuning data flows to maximize performance and minimize latency.

Alert and Automate: By configuring out-of-the-box alerts for different types of metrics, businesses can get updates on the status and performance of the data flows. Workflows can be automated for performing correction actions if errors or failures occur. Compensating data flows can be triggered by tapping into error or status streams to perform remedial actions.

Dashboards: Striim also provide dashboards to create wizards and real-time data visualizations such as heat maps, pie charts, bar charts, and so on.

Some of the other benefits of going with Striim include access to a hundred connectors to access data sources. It is highly scalable and available, allows real-time data processing and ETL using SQL, and can be deployed anywhere.

Indium–A Striim Partner

Indium Software is a Striim implementation partner providing Striim resources and expertise for real-time integration. Our data and analytics solutions experts leverage Striim capabilities to empower business users with insights needed to improve their efficiency and responsiveness.

Author: Indium
Indium Software is a leading digital engineering company that provides Application Engineering, Cloud Engineering, Data and Analytics, DevOps, Digital Assurance, and Gaming services. We assist companies in their digital transformation journey at every stage of digital adoption, allowing them to become market leaders.