Improving efficiency and productivity from data analytics

Preduplicating data allows greater efficiencies without the risk of data ingestion limits or escalating server costs.

Rick Watts, Relationship Manager


Improving efficiency and productivity from data analytics

Thursday, December 06, 2018

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Today’s enterprises face the challenge of deciding how to invest in their future big data strategy.

Transformation Glamour

While it may be tempting to quickly develop a transformation strategy, the basic steps of automation and investment often get lost in the glamour of “transformation”.

Before outlining infrastructure and data management costs, talent acquisition in data analytics and engineering, and the necessary strategic commitment, you should first determine if your organization well-suited to actually take advantage of its data. Through automation (improving operational efficiency and productivity), the development of new information (investing in new data to align business decisions with telemetry), or business transformation (the development of new products and services to drive innovation and new revenue streams).

Automation

Automation can generate ROI by streamlining business processes and improving operational efficiency, thus reducing costs. While Amazon dominates markets where it can use its automation to create efficiency at scale, Walmart, too, is flexing its muscle redefining responsibilities using scanning robots and other automated technologies.

The practice of automation goes beyond reducing manual labor and can be leveraged to further enable analytics and operations teams. LogZilla’s Network Event Orchestrator (NEO) engine assesses the severity and next steps based on data gathered from external systems and takes appropriate actions to automatically bring the affected system back into service. Using machine learning, this detection process can be automated and made more accurate over time, freeing up resources to perform more strategic analysis.

Generating new information to improve business operations should be your top goal and using data to create new value builds on automation’s virtues and puts an organization on the path to transformation.

The commitment to achieving more information value from data requires that more data be collected, stored, and analyzed. According to Tech Pro Research, 61% of companies aren’t using any big data solution, thus potentially missing out on insights that could inform business decisions. LogZilla NEO’s preduplication™ feature is the industry’s only solution that can pre-process data at 800,000 events per second, or in easier terms, 36TB per server, per day – never hitting server limits, or worrying about leaving data ‘out in the cold.’

Are You Ready?

Organizations striving for transformative use of data are inherently data-driven: they ingest more and different types of data than counterparts, and develop a culture rooted in agility. Retail marketing, for example, has transformed the industry with geolocation which can be used for presenting ads, relevant content, promotions, or coupons creating more tailored and relevant marketing for potential customers.

In the journey to transformation, ensuring your data operations infrastructure has the speed, scale and capacity to harness operational insights – while adapting to the complexities of your evolving business – is critical.

Ensure you can meet your organizations challenges by having the ability to scale data operations to extract insight – and value – from both real-time streaming events and historical analytics.

LogZilla NEO – ten minutes to 100% operability with the world’s fastest scale.



Rick Watts

Rick Watts

Relationship Manager
Jacksonville Beach, FL,

About Rick

Rick Watts brings his 20 years of selling to grow the entire southeast and southwest regions for LogZilla's sales team. Rooted deeply in developing strong relationships with customers as reflected in his two decades leading insurance sales, Watts seeks to educate customers on solutions around todays most pressing financial and risk-based network challenges. Watts resides in Florida
Tags: Big data , Transformation , Automation , Data analytics , Machine learning , Preduplication , Operations , Scale

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