White Paper

Getting Real Value from Real-Time Streaming Analytics

Getting Real Value from Real-Time Streaming Analytics

Enterprises and IoT applications can benefit immensely from real-time streaming analytics by visualizing the business in real-time, cutting preventable losses, detecting urgent situations and automating immediate actions.

Highlights:

  • What is real-time streaming analytics?
  • What are distinctive characteristics of real-time streaming analytics?
  • How real-time streaming analytics can add value to business?
  • Recommendations on design, approaches and implementation of real-time streaming analytics

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A Future-Proof Architecture for Streaming Data Analytics

A Future-Proof Architecture for Streaming Data Analytics

Are you ready to reap the benefits of streaming analytics, but are worried about investing in new technology that could rapidly be surpassed or become outdated?

Learn how to leverage the steady flow of advanced real-time streaming data analytics (RTSA) application development technologies and future-proof the solution.

Highlights:

  • Benefits of real- time streaming analytics (RTSA)
  • Architecture of an RTSA platform
  • How to future-proof an RTSA platform?

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The Build vs. Buy Decision: Exploring a Third Alternative

The Build vs. Buy Decision: Exploring a Third Alternative

As enterprises realize the power of real-time information, streaming analytics platforms are fast becoming a must-have technology for enterprises. This whitepaper explores the classic IT conundrum of build vs buy, specifically in terms of acquiring a real-time streaming analytics platform.

Highlights:

  • Pros and cons of doing-it-yourself against the option of buying a pre-built solution
  • Four categories of buying options
  • The Third Alternative: “The Best of Both Worlds”

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Real-Time Streaming Analytics

Real-Time Streaming Analytics

Here is a one stop source for all that you wanted to learn about real-time streaming analytics.

This comprehensive guide by Inside BIG DATA explores the genesis of streaming analytics and the business value of real-time streaming for enterprises for different use cases. The paper shares how businesses are selecting a streaming architecture along with a few case studies. It also provides an overview on StreamAnalytix- industry’s only multi-engine streaming analytics platform based on open source technology stack.

Read this guide to learn how you can implement and derive business value from real- time streaming analytics.

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Driving Business Value from Real-Time Streaming Analytics

Driving Business Value from Real-Time Streaming Analytics

Driving Business Value from Real-Time Streaming Analytics

Is your data value decreasing with each increment of delay, becoming less a force for rapid response than a resource for diagnostics and descriptive reports of the past?

Learn how enterprises are tapping into unstructured, real-time data sources that create a potential goldmine of information.

This white paper explores different real-time use cases of real-time streaming analytics across various industry verticals.

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Data Science for Real-Time Streaming Analytics

Data Science for Real-Time Streaming Analytics

Are you looking to extract business value in real-time from data in motion? Data analytics forms a crucial part of Real-time Streaming Analytics (RTSA) that allows for the collection, integration, analysis and visualization of data in real-time.

This white paper explores different data science models and methods for streaming analytics.

Highlights:

  • Types of data analytics
  • Batch vs. streaming data analytics
  • How to extract insights from data in motion
  • Offline vs. online modeling
  • Challenges posed by streaming analytics

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IoT: The Trigger for Streaming Analytics

IoT: The Trigger for Streaming Analytics

An Ovum white paper for Impetus StreamAnalytix

The Internet of Things (IoT) is becoming ubiquitous. More than just a curious trend, enterprises have a huge stake in harnessing IoT, as it could provide greater visibility into the operations and challenges that they already face.

While the IoT data helps enterprises improve their ability to solve the operational challenges and create new business opportunities, processing the data and using it to drive actionable strategy in real-time is a challenge. Low-cost streaming analytics plays a vital role interpreting IoT data.

This white paper explores different use cases for streaming analytics involving IoT spanning a wide range of industries.

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Top 6 Considerations for a Streaming Analytics Platform

Top 6 Considerations for a Streaming Analytics Platform

All data is first generated in real-time, be it financial transactions, sensor data, web clickstreams, geolocation data, weather reports, market data, social media, and other event streams. A real-time streaming analytics platform can help business gain insights from the high-velocity flow of data as they originate, optimize decisions, improve business insights, and accelerate responses to critical events.

This white paper explores the key considerations while choosing a real-time streaming analytics platform.

Highlights:

  • Visual low code development
  • Application lifecycle management
  • Support for ‘real-time’, ‘near real-time’, and batch processing
  • Technology agnostic and open source enabled

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Guide to Real-time Anomaly Detection for Enterprise Data

Guide to Real-time Anomaly Detection for Enterprise Data

Anomaly detection forms an essential component of real-time analytics, which help enterprises gain significant actionable insights across a wide variety of application domains. However, detecting anomalies accurately can be difficult. As systems evolve, behaviors change, and software gets updated, the system needs to be upgraded continuously to detect an anomaly effectively.

This white paper explores the know-hows of big data anomaly detection in real-time.

Highlights:

  • The importance of big data anomaly detection
  • How to build an anomaly detection model
  • A view of the platform approach to real-time anomaly detection
  • How StreamAnalytix can help in real-time anomaly detection

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Impetus Technologies’ StreamAnalytix Lite narrows the Spark talent gap -Ovum Analyst Research Note

Impetus Technologies’ StreamAnalytix Lite narrows the Spark talent gap -Ovum Analyst Research Note

Spark has eclipsed MapReduce as the preferred processing engine in the enterprise due to its speed, real-time data processing capabilities, and utility in machine learning applications. However, despite this rapid growth in popularity, there is a lag in the availability of Spark technical talent and skills.

In this research paper, Ovum analyst explores how StreamAnalytix Lite bridges this talent gap, making Spark development accessible to developers and other semitechnical personas who do not have pre-existing in-depth Spark knowledge or skills.

StreamAnalytix Lite comes with a highly visual Integrated Development Environment (IDE), which enables users to build, test, and run Spark applications with a code-free drag-and-drop interface.

Download the paper to learn why free and easy to download StreamAnalytix Lite is a natural stepping stone to the fully-featured paid StreamAnalytix platform.

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