A strategic guide to putting your data to work with search and AI
How IT leaders can improve digital customer experiences, increase operational resilience, and reduce cyber risk by putting existing, untapped data to work in real time with the precision of search and the intelligence of AI
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Let's dive in
As a consumer and an IT leader, you expect seamless and secure interactions with the multitude of platforms you use daily — applications, websites, emails, texts, and video calls. Likewise, as an IT leader, it’s your responsibility to ensure the availability and security of these underlying systems. This not only elevates customer satisfaction but also empowers your employees, enabling you to achieve your business goals.
Organizations that find answers from their data in real time are:1
- 8x more likely to grow revenue by 20% or more in these ways
- 1.4 times more likely to uncover new revenue streams
- 1.6 times more likely to create data-driven experiences
- 1.8 times more likely to commercialize their data
With the continuous requirement to enhance visibility into the performance of crucial applications and infrastructure, boost security measures, and improve the discovery of relevant information, you have a lot on your plate!
So, what if we told you there's an untapped opportunity to streamline your tech stack and simultaneously realize cost savings? Read on to find out everything you need to know to do exactly that.
Table of Contents
Business problems = data problems
Data challenges and business complexities continue to accelerate
Why you need to combat these challenges
Combat these challenges with the precision of search and the intelligence of AI
What to look for in a search and AI platform
Business problems = data problems
As an IT leader, you are expected to optimize enterprise applications and infrastructure for availability and performance.
The average application, comprising of 50 to 100 services with multiple deployments, can generate more than 300 GB of data per hour during an incident or outage.2 And when IT downtime can cut enterprise profit by 9%,3 every second of an outage matters. Imagine if a grocery store's online ordering system went down days before a big holiday. If the stress of the holiday season wasn't enough, this would certainly make for some unhappy customers. Unplanned downtime not only leaves a bad taste in customers' mouths (no pun intended) but can easily amount to millions of dollars lost.4
These are data problems.
As an IT leader, you’re also expected to prevent security threats and detect and resolve incidents quickly when they do occur.
The average Fortune 500 enterprise generates more than 10TB of security events per month5 You and your team are always sifting through the exponential mountains of security data, anticipating the next threat. The impact it could have on your brand and the disruption it would have on your organization’s day-to-day operations is enough to keep any IT leader up at night.
These are data problems.
IT leaders are expected to connect the right people and teams with the right information, at the right time regardless of where the information is, or the format of the data. For example, a customer needs help installing their video doorbell. By interacting with a self-service experience, the customer gets frustrated that they have to enter in their product number to even start the troubleshooting process. The experience is cumbersome and clunky. About 77% of consumers say that offering poor self-service support is worse than not offering any at all since it wastes time.6
These are data problems.
Sure, all of these challenges are connected to data, but they can also be solved with data. When the average enterprise stores more than 71PB of structured and unstructured data on-premises alone, not even including cloud,8 there are plenty of answers just waiting to be uncovered. That data could be hiding key insights into business growth, indicators of compromise, and everything in between. However, this data shouldn’t just be stored. It needs to be put to work.
Unfortunately, only 32% of data within organizations is actively being put to work9 today, which leaves an undesirable amount of data taking up space and costing money to store without adding any value. Being able to utilize this untapped data will enable you to keep customers happy, keep your systems up and running, and keep your organization protected. But how?
To address these data challenges, organizations need a way to derive value from data continuously, in real time.
With the precision of search and the intelligence of AI, you can enable users to find the answers that matter from all of your data in real time, at scale. Search technology by design is built to surface the most relevant pieces of information at speed and scale, but search technology is only capable of generating lists of results. On the other hand, generative AI can generate exact answers using its computational power and intelligence, but it has no context of your organization’s knowledge.
When you combine the precision of search with the intelligence of AI and your proprietary data, you can find answers to enterprise problems from all data, in real-time, and at scale.
Search combined with the intelligence of AI is able to quickly ingest messy data at enormous scale and enable all types of real-time analytics on top of that data. Even when data is complex, the type of analysis required isn’t known ahead of time, or analytics are needed in real time, the combination of search and AI is able to take on the challenge.
How do you put search and AI to work? Read on to find out everything you need to know in order to analyze your data, extract insights, and continuously derive value in real time. But first, a bit of insight into the challenges organizations are facing.
Data challenges and business complexities continue to accelerate
Organizations of all sizes are experiencing exponential growth of unstructured data. You’re most likely dealing with at least one of the challenges below:
- Customer and employee expectations are higher than ever
In fact, 84% of customers expect11 and hope for brands to adopt new digital solutions to deliver products and services to them. And when it comes to employees, they need their technology stack to work for them and integrate disparate systems across the organization in order to feel empowered to do their best work. IT teams must monitor all systems to ensure problems are diagnosed and fixed quickly, which leads to an exponential amount of data that must be monitored.
- Security attacks are on the rise
Security attacks are on the rise with a 20% increase in attacks from 2022 to 2023,12 and have been further exacerbated by AI.13 IT needs to partner closely with security teams to ensure security is unified across the business and built into employee education. Attempted breaches and attacks targeted at individual employees are only expected to increase.
- Shift in emphasis to providing business value
The days of IT simply being a cost center are in the past. IT teams are shifting from just delivering technologies to optimizing them.14 IT is now expected to maximize the organization’s technology investments to improve operational efficiencies and, ultimately, generate tangible value. All this to say, IT teams are expected to substantially help generate revenue.
- Digital transformation initiatives continue to influence IT strategies
Continues to influence IT strategies as organizations move their processes to more digitized environments and workflows. With the goal of aligning growing data in real time across environments and platforms, organizations have a lot more data to manage, process, and extract insight from to transform their business and meet employee and consumer expectations.
With these complexities, come business goals you need to meet.
The need to elevate customer and employee experiences to keep customers satisfied. This relies on seamless information discovery, holistic visibility into IT systems, and strong data protection.
The need to improve operational resilience to keep systems reliably up and running, which depends on resilient data storage and comprehensive insights into IT systems and security events data.
The need to reduce security risks to keep systems secure and sensitive data protected, which requires a secure data store and comprehensive monitoring of security events and IT systems.
Unfortunately, most organizations are faced with a mountain (or an iceberg in this case) of underlying data problems that continuously compound until you’re just overwhelmed with data that doesn’t work for you.
Your giant mountain of data leads to a mountain of tools tasked with managing and making use of all that data. This leaves you with an even bigger problem that is hidden from plain sight.
The traditional tools and methods you deploy to solve business problems lead to:
- An inability to iterate through data. Slow iteration speeds can lead to inaccurate and irrelevant results and scalability issues. This impacts the ability to iterate through your data in real time. And when you can’t iterate, your data is useless.
- A closed data stack. With different products for each environment, there are limited data types that can be supported by each product within each environment. That means that you won’t be able to correlate data across those environments; you’ll never be able to get a holistic view of all of your data. When you want to update your product, you will need to rip and replace the entire system.
- Siloed and redundant data. When you have all of these different products that each perform a few tasks, you’re getting fractured user experiences for your data teams, increased costs with different pricing for each module, and ultimately, siloed and redundant data. All of this leads to increased security risk, unplanned downtime, and poor customer experiences. You then have a sizable data tech stack that doesn’t allow for your data to be used across multiple environments.
Demands escalated by ongoing data challenges
Why you need to combat these challenges
With the exponential increase in data, we’ll see an increase in the complexity of security threats, requiring more monitoring. As the use of SaaS solutions increases, so will the number of cloud providers you use, and so will the number of partners using those solutions and providers. Organizations are finding it more important than ever to have a tech stack that consolidates solutions and saves money.
480 EB of data produced daily by 2025 (1 EB = 1000 PB = 1,000,000 TB)15
Organizations that use real-time data for the right purpose are:16
more likely to grow revenue by 20% or more in these ways
times more likely to create data-driven experiences
times more likely to uncover new revenue streams
times more likely to commercialize their data
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Combat these challenges with the precision of search and the intelligence of AI
The way you make use of all of this data is through a solution that combines the precision of search with the intelligence of AI that is delivered on a single platform with a flexible, scalable architecture.
When it comes to your data, search and AI help you:
By exploring the data seamlessly within one unified platform with the intelligence of IA, you can iteratively refine the information and apply relevance to the data insights in real time. This enables you to derive value from all of your data to address broader business challenges, opportunities, and priorities, like enhancing customer experiences, improving resiliency, and mitigating security risks.
The precision of search and the intelligence of AI gives your enterprise:
- Speed: Just like Google, type your query and press enter to get answers in natural language from all of your data sources. Not seeing what you’re looking for? Just enter another query and get those results just as fast.
- Scalability: As your data grows (and it will grow!), the combination of search and AI allows you to seamlessly meet your needs at any scale, with no hardware-driven limitations.
- Relevance: The context of a search will be different between a security analyst conducting a search versus an SRE versus a customer. Context matters. Search and AI provide relevant, contextual results.
- Iterative exploration: All of these aspects combined gives you the opportunity to iteratively explore and analyze all of your data. You are able to slice and dice in different ways by searching different terms.
How your solution goes about putting your data to work in real time matters. Also, how that solution is delivered matters. Your search and AI solution needs to be simple, flexible, and work across all of your environments without you needing to move your data from where it is.
What to look for in a search and AI platform
When comparing solutions, we’ve compiled the many features you should consider.
A solution that combines the relevance of search with the intelligence of AI that is delivered on one platform provides simplicity through an end-to-end experience with your data lifecycle. From ingest to insights, you’re using one data store that uses lifecycle management, search capabilities, access rights, and machine learning. And all of this needs to encompass data from the back end to the front end of your systems.
With a single, unified platform, you get:
A unified user experience across all of your solutions and data stores. With one, single-user experience, IT teams don’t need to relearn a new tool each time a new solution is deployed.
Uniform resource-based pricing means you only pay for the resources you consume, independent of how you use the data platform. This is essential as you scale and add more users (and, of course, more data), knowing you’re only paying for the additional resources you consume.
A single data store reduces data redundancy by storing all of your data across different solutions. Since observability data can be identical to security data, there’s no need to store that twice and waste resources. With a single data store, you decrease licensing and storage, hardware, and infrastructure costs.
A common schema allows you to bring data together that may not reside in the same place, doubling the value of your data. For example, when it comes to user behavior monitoring, you’re monitoring customers to understand their buying behavior. But this data is also useful when it comes to security. You can monitor the same data to look for anomalies and patterns. Are these humans interacting with your application? Or bots? Bringing together all these solutions and all of your data allows you to unlock these insights that you may have missed if they weren’t correlated.
Unlock your data beneath the surface
The precision of search combined with the intelligence of AI can transform your big, messy data problems into business results by helping you continuously derive value from petabytes of data — in real time. And you don't have to break the (IT) bank because you only need one, flexible platform that combines the precision of search and the intelligence of AI to do it.
Learn what you can accomplish with the right platform.
