Big Data: How AI Analytics Drives Better Business


“Data-driven” is the latest buzzword in organizations in which data-based decision making is directly connected to business success. According to Gartner’s Hype Cycle, more than 77% of the C-suite now say data science is critical to their organization meeting strategic objectives. 

For top organizations looking to adopt a data-driven culture to stay competitive, what does that mean? The term evokes images of data analysts huddled in a dimly lit office, watching numbers and visualizations pass on a dashboard as their observant eyes search for anomalies. 

But as data scientists and analysts become increasingly expensive and in high demand, many organizations are questioning why these highly skilled knowledge workers should be relegated to a role where they observe dashboards and react to changes? 

Companies that lead in data-driven organizational analytics know that for knowledge workers to deliver value, they need tools that free them from laborious tasks to spend more time on meaningful strategic initiatives and less time wrangling data for insights.

Growth of Big Data 


Industry analysts predict that digital data creation will increase by 23% per year through 2025. The global market for Big Data is expected to exceed $448 billion by 2027. So what’s driving this growth? Businesses across the globe now recognize the force multiplier that data-driven business intelligence represents to improve business outcomes. 

The only legitimate restraining forces for the development of Big Data are the costs associated with staffing data science and business intelligence competencies and the time-intensive nature of analytics work. 

With over 81% of companies planning to expand their Big Data capabilities and data science departments in the next few years, the competition for resources will only increase. 

Traditional BI Dashboards Can’t Keep Up With Big Data


In today’s data-driven economy, managers struggle to keep up with the myriad of business intelligence reports from traditional BI tools – which fail to effectively and efficiently analyze and interpret the data in real-time. The fact is, conventional BI approaches and tools were not designed for and are not suited for the growth of Big Data.

While most of the existing BI solutions can process and store a vast amount of data with many dimensions, they don’t offer analysts a manageable way to get real-time business insights, and they certainly don’t help data science teams predict the future. 

Traditional BI tools lack detailed analysis, offer little correlation, and don’t provide real-time actionable insights. That leaves data science teams and business analysts spending hours with data stores instead of working on delivering value with predictive analytics. 

Gain Business Value With Big Data Empowered by AI Analytics


Many companies overextend their BI tools and teams on use cases they were never built to handle. That leaves knowledge workers trying to extract insights from traditional solutions. To put that in perspective, it’s like tying an anchor around their waist and asking them to swim. 

The answer is extending business intelligence capabilities with analytics capabilities empowered by AI and machine learning. Rather than developing new views, models, and dashboards, teams leveraging AI analytics gain real-time actionable insights to react to change and predict the future. 


Big Data AI Analytics With Anodot


Regardless of the industry or how far along your business might be in its data analytics journey, Anodot’s AI-powered analytics can empower your knowledge workers to focus on leveraging business insights to deliver value. Instead of digging into dashboards for answers, Anodot delivers the answers to them, automatically. 

Anodot monitors 100% of business data in real time, autonomously learning the normal behavior of business metrics. Our patented anomaly detection technology distills billions of data events into a single, unified source of truth without the extra noise that can leave teams flatfooted. 

AI Analytics for Big Data

Anodot delivers the full context needed for BI teams to make impactful decisions by featuring a robust correlation engine that groups anomalies and identifies contributing factors. This helps teams know first, before incidents impact customers or revenue. 

Data-driven companies use Anodot’s machine learning platform to detect business incidents in real-time, helping slash time to detect by 80 percent and reduce false-positive alert noise by as much as 95 percent.

Written by Anodot

Anodot leads in Autonomous Business Monitoring, offering real-time incident detection and innovative cloud cost management solutions with a primary focus on partnerships and MSP collaboration. Our machine learning platform not only identifies business incidents promptly but also optimizes cloud resources, reducing waste. By reducing alert noise by up to 95 percent and slashing time to detection by as much as 80 percent, Anodot has helped customers recover millions in time and revenue.

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