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Published September 2, 2022

Why Organizations Need Hyperscale Data Analytics Solutions

By Ocient Staff

Organizations of all shapes and sizes have a plethora of data available at their fingertips. From numerous network events challenging data security to multi-dimensional data collected from real-time monitoring devices, companies are confronted with a vast array of information that would inform decision-making, but which legacy and even current tools are unable to process. Decision makers who try to gain insight by accessing numerous platforms and pulling a variety of reports may find themselves overwhelmed by the sheer amount of data, both structured and semi-structured.

As the volume of data grows, so does the potential to do things like better meet customer needs, predict severe weather patterns, create safer cars, and solve significant challenges. This is why hyperscale analysis of data within large organizations is vital for business and organizational success.

What Is Hyperscale Analysis? 

Hyperscaling is the ability of technologies or systems to handle large-scale entities, and to quickly grow, or scale, as additional components are added. When discussing hyperscaling for analysis, it means just that: The ability to analyze large-scale information, and to scale the analysis elements of your organization – without limits – regardless of the additional elements that are put into place. This is important for a variety of reasons.

The Importance of Hyperscale Data Analytics Solutions

The goal of most businesses is growth. For virtually every element, as a business grows, it must put more technology and processes into place with the goal of expediting process flows. With that growth, there are more employees involved, more customers, and more revenue. Tracking all of this is important for decision makers because it enables them to make well-informed recommendations regarding how to best move forward.

For industries such as AdTech, financial services, and telecommunications, the sheer amount of data their operations generate can exceed their ability to analyze it in a meaningful way. While the systems that they’ve implemented are helping the organization to operate on a daily basis, the insights locked inside of those massive datasets could be helping them to operate more efficiently, increase revenues, create new products, identify new markets, and even accelerate exponential growth.

A Process That Grows with The Business

With business growth, each element needs to be scalable. If it is not, expansion is stifled and opportunities are lost. Data analytics solutions are no different. If the solution cannot scale with the growth of data then valuable information is inaccessible – information that is important for making decisions affecting any aspect of business – anywhere from production to marketing. If only a fraction of data is being aggregated and analyzed, it is unlikely the decision makers are making fully-informed business decisions.

Additionally, this lack of valuable information results in lost opportunities: Marketing data that could better inform research and development. A car dealership that not only knows when a vehicle is due for service, but proactively orders parts and services needing attention before the vehicle owner arrives for their appointment. The ability to leverage data from one line of business to inform another. The opportunities are as unlimited as the data that is analyzed within the enterprise.

Plan for Growth

When you design a solution that is scalable as business growth begins and the organization continues to thrive, there is no need to repeatedly replace outgrown systems. Investing in data analytics solutions that can both take on existing hyperscale data sets and quickly scale with your business will save you both time and money in the long run. 

Speed is Everything

Employees are busy. Whether it’s the staff pulling the data, the analysts reviewing and interpreting the data, or the key decision makers who utilize the data to plan, each employee needs the information fast. Hyperscale data analysis allows for information, at mass scales, to be aggregated quickly through tailored query optimization. This enables analysts to pull exactly what needs to be analyzed and provides the decision maker with the information needed to make the best business choice.

Who Does Hyperscale Data Analysis Benefit?

Organizations possess an array of data, and the larger they are, the more data they have. Hyperscale analysis works well for organizations with significant amounts of data. Oftentimes, this data is retrieved from a variety of sources – from  moving vehicles, mobile devices, content delivery networks, ad exchanges, and more, in the form of XML, JSON, CVS, and other semi-structured formats. Hyperscale data analytics solutions enable organizations to have all of their insights within one platform, making them easily accessible and digestible. This allows for employees to gather a full scope of insights, across various departments, process flows, or campaigns. 

This includes organizations in industries such as:

  • AdTech – More than 10 million digital ad placement auctions per second, 26 petabytes of data are generated per day – about 1,000 petabytes per month.
  • Financial Services – Trillions of records to analyze using sophisticated science, including full-resolution market tick data across decades of historical data points.
  • Telecommunications – The need to track data generated by billions of devices, each generating gigabytes of metadata per day – totalling roughly 150 petabytes of data per year, and growing rapidly with continued innovation around 5G.
  • Geospatial – In automotive alone, smart vehicles are generating 500 MB per vehicle per day, which is over 487,000 petabytes of data per year globally.
  • Government – With the advent of gigabit household connections and 5G networks, governments must operate at scales that can reach hundreds of terabytes of new data every hour for lawful intercept, while law enforcement requires more interactive response times to fulfill their duties.

Beyond the organization as a whole, having data sources augmented by query optimization and possessing the ability to be surface level, or incredibly granular, is important for individuals to ensure they are looking at the impacts each decision makes within the organization.

How Can Hyperscale Analysis Be Utilized? 

Increased historical analysis at full resolution

Finding a virtual needle in a haystack of records spanning decades is completely different than finding them across the span of just a few months. This provides an organization with granular insights from a longer lookback window to understand behavioral patterns and trends that were previously infeasible.

Predictive modeling on hyperscale datasets

From ad exchanges to weather data to cybersecurity risks, predicting the future from a veritable firehose of machine-generated data is a great application for hyperscale data analytics solutions. Such solutions provide the ability to ingest and leverage a variety of data sources in near real-time to predict what will happen next.

Understanding patterns for objects in motion

Geospatial analytics and understanding how things are moving around the earth – whether they are cars, airplanes, boats, or a variety of other things – hold valuable data that many organizations and public sector agencies have yet to fully tap into. Hyperscale data analysis opens new windows of understanding.

Data: The Cells of an Organization

Make strong, evidence-based decisions with powerful data analytics solutions that grow with your company. 

Ocient is the hyperscale data analytics provider that delivers use-case-driven solutions, optimized storage with a smaller footprint, and a high-performance data warehouse platform that offers limitless scale for compute-intensive data analysis at hyperscale. Schedule a demo to get started!