In the digital age, enterprises cannot achieve business success without utilizing their data. Successful companies need data about the current market conditions, customer requirements, and competitors. Without real-time data analytics, companies cannot transform their massive data into immediate and meaningful business insights.

Gartner defines real-time analytics as the “discipline that applies logic and mathematics to data to provide insights for making better decisions quickly.” In a data-driven business environment, real-time analytics is the business tool that enterprises are leveraging to improve their decision-making skills and gain a competitive advantage in the market.

Using real-time analytics, organizations can now extract actionable insights to improve their business processes and drive customer engagement. How do real-time analytics drive business value? As compared to “historical” data analytics, real-time analytics enable enterprises to immediately and proactively respond to market-driven changes.

How do you make real-time analytics more effective? By feeding real-time analytics solutions with real-time available data with the lowest latency. In a low-latency environment, there are zero data delays or lags – thus ensuring that only insights (relevant to the business) are extracted.

Among the latest innovations from Google Cloud, AlloyDB Omni is the downloadable version of AlloyDB – designed to run anywhere including data centers, laptops, cloud platforms, and on edge devices.

In this blog, we’ll explore how real-time data analytics with AlloyDB Omni delivers business value.

Real-time analytics with AlloyDB Omni

With AlloyDB Omni, organizations can extract real-time insights from operational data – without the need to copy data to the warehouse. AlloyDB’s columnar engine maintains frequently queried data in its in-memory columnar format.

How is this beneficial? This ensures faster processing of operational data for business intelligence and hybrid transactional & analytical processing (HTAP) workloads. Going by Google’s performance tests, AlloyDB Omni delivers 100-times faster analytical queries as compared to PostgreSQL.

Additionally, AlloyDB Omni leverages machine learning to organize data automatically between row and columnar formats, switch execution plans, and convert data formats.

Business impact of real-time Analytics

Why is real-time analytics valuable to organizations? Simply put, it enables immediate prediction of future trends and patterns, thus empowering better decisions. Here are four areas where real-time analytics can create a major business impact:

1. Accurate customer insights

Customer-based real-time insights provide companies with valuable information on their customer’s needs – and how they are currently using their products or services. With real-time analytics, companies can now predict customer behavior and improve their business decisions.

These data-driven insights empower enterprises with the ability to:

• Understand their customers and their current preferences.
• Identify relevant customer segments that are most likely to purchase their products or services.
• Know their customer’s current pain points and challenges.
• Drive customer loyalty for the brand.

2. Targeted marketing campaigns

Using real-time data analytics, marketing teams can now design a targeted marketing campaign to increase their customer base. For instance, predictive analytics can help them identify potential customers based on prevailing data trends.

Using data analytics tools like Google Analytics, companies can now analyze their website traffic data – along with the customer’s social media activity and previous transactions. 

3. Improved business agility

Apart from faster decision-making, real-time analytics can also improve business agility. In a fast-changing business environment, business leaders and executives have to respond proactively and quickly to adapt their operations and make smarter decisions. They can no longer depend on old (or outdated) data to improve their business processes.

Business agility also encompasses business goals and strategies – along with the ability to identify market opportunities – or threats. With real-time data, employees are also empowered to make the right decisions in their business functions.

4. Information security

Real-time analytics can enhance information security by analyzing software usage and network traffic. With these data insights, security teams can identify any security risks – and mitigate them before they lead to any data breach or security incident. 

Besides, real-time analytics enable organizations to comply with security-related regulations regarding data privacy. By analyzing the flow of data, analytics tools can detect any deviation or anomaly, which can indicate a violation.

As is evident, organizations cannot implement real-time analytics on outdated systems and data silos. They need an efficient data modernization strategy to improve their data infrastructure – which is critical for efficient analytics. 

Why is Data modernization important for Real-time Analytics?

Data modernization is not just about upgrading the existing data architecture. It is also about completely “rethinking” it. Data modernization is clearly necessary to facilitate real-time analytics. Modernization is also crucial for organizations to use their growing data volumes more optimally to drive business results.

Here are some of the business benefits of data modernization for real-time analytics:

• Providing real-time insights and metrics to drive informed business decision-making.
• Aggregating and integrating data from disparate sources – into a single data repository (to be utilized for real-time analytics).
• Democratizing real-time analytics and making it accessible to all decision-makers.
• Building business agility for organizations to adapt to changing business environments.
• Improving data quality by eliminating ‘siloed’ data and updating that data for real-time analytics.

Data modernization has its share of challenges for real-time analytics including:

• Presence of outdated legacy systems that do not seamlessly integrate with modern data technologies.
• Growing volumes and complexity of real-time data that hinder analytics.
• High implementation costs for enterprises with loads of legacy data and siloed systems.
• A growing shortage of data professionals skilled in executing modernization projects.

With the aid of a technology partner, organizations can maximize their business value from data-driven insights. 

How Onix enables a Data-driven organization with Real-time analytics

In summary, Google’s AlloyDB Omni provides a unified platform to organize and process data with its columnar engine. This improves performance while minimizing the management overload.

Onix’s data analytics solution can drive business value across organizations with benefits like:

• Improved business agility
• Freedom from legacy systems
• Faster technological innovation

We work closely with our customers across their entire modernization journey which includes data modernization, data migration, predictive analytics, and prescriptive analytics.  With this analytics modernization solution, organizations can easily democratize their data for better decision-making and harness the vast potential of their data. The Onix team can evaluate your data requirements, mobilize data migration and modernization, and extract valuable insights from real-time data. Here is a successful customer story of how the Canada-based Labour Market Information Council (LMIC) implemented its data modernization.

Are you prepared to transform into a data-driven organization? Request for a free data assessment today.