Real-time analytics is a discipline that revolves around swiftly processing and interpreting data as it’s generated, providing instant insights and actionable information useful for improving business decisions. In contrast, traditional analytics relies on batch processing, leading to delayed results. Real-time analytics empowers businesses, industries, and even sports venues to gain a competitive edge, optimize operations, and elevate customer experiences.

To demonstrate its practical application, let’s transport ourselves to Wrigley Field on a Sunday afternoon, where the Chicago crosstown rivals are about to compete. As fans eagerly enter the ballpark, an advanced fan occupancy dashboard diligently tracks each entry into the venue. This real-time data collection and analysis play a pivotal role in ensuring a seamless and enjoyable experience for both fans and event organizers.

Assess Your Infrastructure for Scalability

To successfully implement real-time analytics, organizations – including professional baseball teams – must establish a scalable data infrastructure. Creating a scalable data infrastructure involves building a skilled team of data engineers and selecting the appropriate technology stack. Before delving into real-time analytics, it’s crucial for organizations to conduct a thorough assessment of your current infrastructure.

This assessment entails evaluating the scalability of existing data systems to ascertain their ability to handle the growing volumes of data. Moreover, the data processing and storage systems, including cloud data warehouses, must demonstrate resilience to manage the continuous influx of data without compromising performance. By ensuring a robust and scalable data infrastructure, organizations can lay the groundwork for effective real-time analytics and gain valuable insights from high-velocity data streams. This also applies to incoming data. An organization’s ability to make decisions will be impacted by how quickly they can factor in new information as it arises; thus, being able to ingest large amounts of data as soon as it becomes available is a vital capability.

Ensure Data Quality and Governance

As an organization begins to ingest and process data in real-time, a standardized approach to data governance becomes essential. Data governance is the process of creating an accountability framework and designating decision rights around an organization’s data with the intention of ensuring the appropriate creation, consumption, and management thereof. Users need access to relevant, high-quality data in a timely manner so they can take action. By implementing data governance policies, organizations can define metrics around data accuracy and work to improve those.

Starting a data governance process requires first identifying essential data. A retail company, for instance, may consider customer purchase patterns as key user behavior intel. Maintaining data integrity, using strategies like automated validation rules for data accuracy, is vital to protect this historical data and ensure its usefulness going forward. Setting measurable metrics and monitoring adherence helps in maintaining quality. If data errors exceed a set limit, it triggers a data cleaning process.

Identifying authority for final decisions on data, like a chief data officer or a data governance board, is essential. Their authority should reflect in data access permissions, limiting who can change or view sensitive data. When implementing data governance policies, the organization must consider the type of stored information, its intended use, and the user type. These factors impact data security, privacy, and regulatory compliance.

Confirm Resource Availability

Skilled personnel are equally as important, if not more so, than the foundation of infrastructure and data governance practices. An organization needs to assess if their IT team has the capacity to maintain the tools and processes surrounding real-time analytics. IT personnel must be able to ingest and process this data for instant consumption in a sustainable manner to gain maximum value.

Additionally, “skilled” is a keyword in “skilled personnel.” Does your IT team have the knowledge and experience to handle real-time data analytics, or do you need to look into hiring? Is there someone on the team who can help with upskilling other staff? Make sure you have this people-focused infrastructure in place in conjunction with your data infrastructure.

Identify Business Use Cases

In situations that demand swift decision-making based on extensive data, an organization can realize considerable advantages through the use of real-time analytics. Instantaneous insights derived from data equip businesses to adjust to rapid market changes and strategically place themselves for prosperity.

Pivoting back to Wrigley Field, tracking fan turnout is simply one among potentially 100 business circumstances where real-time analytics can demonstrate its value. The home team’s concession management can promptly assess sales of merchandise and concessions, and they can begin amending their forecast for the next day’s game right away. In tandem, their chief marketing officer could fine-tune marketing strategies based on ticket sale trends, consequently improving stadium fill rates. Beyond that, there are opportunities to delve into game-generated data and player statistics to understand their potential effects on audience behavior.

Furthermore, keep in mind the impact of data lag when you’re exploring your industry or business for typical or standard operations that suffer due to a delay in data access. How about fraud detection? Or even using the power of streaming data to enable enhanced business intelligence, predictive analytics, and machine learning? Identifying these situations will be key in assisting you to unearth the most effective applications of real-time analytics within your enterprise.

Consider Security and Compliance

Whenever changes are made to your digital framework, it’s crucial to tackle possible security threats. Your organization needs to understand the nature of the sensitive data it holds and who has the right to access it. For example, think about a healthcare company managing patient data. There is a necessity for strict controls over access to such sensitive data. The company must ensure that only individuals with the right authorization can access this information. Moreover, they should be thorough in overseeing their cloud service provider and any other related entities that might handle or use this data. This approach safeguards individual privacy and adheres to regulatory standards like HIPAA in the United States.

Depending on the specifics of the data, infrastructure adjustments may also be required to keep in line with data protection rules. Using our Wrigley Field example, there may be collection of personal financial information through ticket and concession sales. In these circumstances, it’s critical to ensure that this data is handled securely and in compliance with all appropriate regulations.

Evaluate Financial Implications and ROI

A crucial aspect of this evaluation involves analyzing the expenses and the ROI associated with the adoption of real-time analytics. There could be monetary considerations related to storage and computational costs, as well as the potential need for more personnel. These factors can fluctuate based on an organization’s existing infrastructure, the skill level of its employees, and the complexity and amount of data to be processed. All these elements need to be balanced against the anticipated ROI and enduring advantages, both quantifiable and qualitative.

Does faster response time decrease operational expenses, enhance customer interactions, or even mitigate security threats? By optimizing operations and reacting swiftly to market fluctuations, organizations can reap significant financial rewards.

Embrace and Implement Real-Time Analytics

Once an organization recognizes an opportunity to apply real-time analytics, the next phase involves identifying and evaluating the data sources that can facilitate this implementation. Subsequently, the organization needs to manage data ingestion, processing, and storage, before defining and constructing any final products. During each of these phases, the choice of suitable tools and technologies is crucial. Your organization should take into account your current infrastructure, maintenance requirements, team skill sets, and any fresh data you wish to integrate into your solution.

Consequently, real-time analytics can give your organization a distinct advantage by allowing data processing as soon as it’s generated, leading to swift and well-informed decision-making. A well-executed implementation has the potential to help anticipate significant issues, boost predictability, optimize operations, and enhance customer relations. Given our society’s data-rich environment, organizations can harness this asset to produce improved solutions and customer experiences. Ready to take action but unsure of the initial steps? Contact 2nd Watch for a complimentary real-time analytics roadmap whiteboarding session.