jKool Blog

14 02, 2017

How You Can Improve Customer Experience With Fast Data Analytics

By |February 14th, 2017|Fast Data, Financial Services, Middleware, monitoring, Real-time Analytics, streaming analytics|0 Comments

In today’s constantly connected world, customers expect more than ever before from the companies they do business with. With the emergence of big data, businesses have been able to better meet and exceed customer expectations thanks to analytics and data science. However, the role of data in your business’ success doesn’t end with big data – now you can take your data mining and analytics to the next level to improve customer service and your business’ overall customer experience faster than you ever thought possible.
Fast data is basically the next step for analysis and application of large data sets (big data). With fast data, big data analytics can be applied to smaller data sets in real time to solve a number of problems for businesses across multiple industries. The goal of fast data analytics services is to mine raw data in real time and provide actionable information that businesses can use to improve their customer experience.
“Fast data analytics allows you to
turn raw data into actionable insights instantly”
Connect with Albert Mavashev
Co-author, CTO & Evangelist at jKool

[…]

2 06, 2016

Strengthen Your Cyber Defense with Big Data and AI

By |June 2nd, 2016|AI, Big Data, Big Data Analytics, cyber security, machine learning, streaming analytics|0 Comments

Security-focused executives need to understand the benefits of these technologies – AI, machine learning, streaming analytics, and advanced visualization techniques – and incorporate them into their planning processes if they are to survive and thrive in the digital age. An integrated approach that brings these technologies together can help turn cyber defenders into cyber […]

23 02, 2016

5 ways to spice up DevOps with jKool

By |February 23rd, 2016|blog, devops, Java, log analytics, operational analytics, operational intelligence, performance monitoring, SaaS, streaming analytics, transaction tracking|0 Comments

Eliminate finger pointing, reduce blame

jKool allows application owners to track and audit transactions; from browser all the way to application servers and middleware. Ability to track transactions is critical if you want to know if your app is slow; and where and why it is slow. How often is the blame placed on you or your team […]

22 02, 2016

Gartner shakes up annual ranking of business analytics tools – TechTarget

By |February 22nd, 2016|Data Science, operational analytics, Real-time Analytics, Spark, streaming analytics|0 Comments

Open source tools, such as R, Python and Spark, are growing in prominence. The number of data sources available to businesses is increasing. And the need for complex event processing and
streaming analytics related to the Internet of Things is growing.

[…] Read the source article at searchbusinessanalytics.techtarget.com
Original Author: edburnstt

12 02, 2016

10 tips for chief analytics officers – ZDNet

By |February 12th, 2016|Apps, Big Data Analytics, Real-time Analytics, streaming analytics, time-series data|0 Comments

Real-time and streaming analytics are getting lots of attention, but keep the real decision time in mind, advised Bill Franks, CAO at Teradata. The IRS, for example, doesn’t worry about real-time because it has weeks to detect fraud before it cuts …

So if a customer’s Web query is followed by a phone call and, […]

11 02, 2016

What does APM have to do with Fast Data?

By |February 11th, 2016|Apps, Big Data, Big Data Analytics, Fast Data, Java, log analytics, operational analytics, operational intelligence, performance monitoring, Real-time Analytics, streaming analytics, transaction tracking|0 Comments

Fast Data is about processing high velocity data in real-time as it happens. Think of Fast Data as Big Data in real-time.

So what does APM have to do with Fast Data?

Everything.

APM is all about processing lots and lots of data as close as possible to real-time.
Tracking transactions, analyzing logs, sampling metrics, figuring out relationships, […]

10 02, 2016

Application Performance in 4 simple steps with jKool

By |February 10th, 2016|Apps, Big Data, Big Data Analytics, performance monitoring, Real-time Analytics, streaming analytics, transaction tracking|0 Comments

Real-time updates on application KPIs
I use “subscribe to events where … output every X seconds” to get a digest of all data streams X number of seconds. Pretty cool feature, especially for those looking for real-time updates on what is happening within your application as it runs.

Queries paired with views
Type in a query and […]

29 01, 2016

Big Data and the Progression toward Streaming Analytics

By |January 29th, 2016|Big Data Analytics, streaming analytics|0 Comments

With today’s limitless data sets and business demands for real-time insight, IT administrators need a new toolkit for drawing insights and even a new language, writes Apurva Dave of Jut.

The post Big Data and the Progression toward Streaming Analytics appeared first on Data Informed.

[…] Read the source article at Data Informed
Original Author: Apurva Dave

21 01, 2016

How Real-Time Data Boosts the Bottom Line

By |January 21st, 2016|Big Data Analytics, Real-time Analytics, streaming analytics|0 Comments

jKool Comments: jKool provides real-time analytics….it ingests streaming data from many sources including: Spark, Kafka, Apache Flume, Logstash, HDFS, Java and more and provides both real-time and historical analytics…

How Real-Time Data Boosts the Bottom Line. Real-time streaming analytics is rapidly becoming the lifeblood of today’s data-driven economy, and savvy businesses are cashing in on […]

5 10, 2015

How IoT can help in more efficient manufacturing

By |October 5th, 2015|Big Data Analytics, Internet of Things, log analytics, streaming analytics|0 Comments

Machines have aided factory workers and supervisors with precise shop floor data management, making the process of monitoring manufacturing plants easier, more efficient, and eventually increasing productivity rates…

 

jKool comments: solutions providing real-time analysis of log data from IoT sources in addition to monitoring metrics and transactions can provide tremendous insight into the data in […]