IoT, Big Data and Advanced Analytics
Big Data => System of Intelligence built using Kafka, Spark & Hadoop
IoT => Edge Analytics
Advanced Analytics => Descriptive -> Predictive -> Prescriptive
Listen to your needs
InfoObjects is your trusted partner in finding which Big Data solution works best for your needs. We are a vendor-neutral, client biased consulting company. Our strong focus is only your use-case and find the best solutions for you.
Resource as a Service
We are there to complement your existing team. Think of it as a hybrid cloud. You approach us when you need additional and advanced help. Like cloud you can scale up and down based on your needs. We understand it is extremely difficult to build expertise in cutting-edge technologies and that’s not your core focus anyway. We take care of technology plumbing for you so that you can focus on delivering value to the business.
Solution as a Service
Sometimes best strategy for you is to completely off-loaded implementation part to us so that you can focus exclusively on business needs. With our center-of-excellence both onsite and offshore, this strategy brings incredible results.
We also advise on cloud hosting.
From Our Blog
For a long time, I was not convinced about the power of the public cloud. Naturally! I, like many others, thought that it was a sideshow, and one which would mostly cater to startups and some medium size companies. However, I discovered I could not be further from the truth. The cloud, from the very More
A lot of technologies change so fast that sometimes the name given to them becomes a misnomer. Big data is one such technology. It's no longer big but fast. Most of the enterprises do not have petabytes of data but they have data which moves very fast. In other words out of volume, velocity, More
Overview Big Data has reached enough maturity that it is ready to create disruption in the enterprise software industry. The first industry that it is going to disrupt is enterprise data warehousing or EDW. EDW technologies came into foray to separate analytical loads from transaction loads. Since memory used to be expensive until recently, transforming More
EMC may not be successful in it's big data strategy but one thing the are successful for sure is coining the term 'Data Lake'. As big data movement is evolving, it's looking more and more like a lake. Gartner in it's most recent hype curve, threw big data out and it created some FUD More
Hadoop has started with data locality as one it's primary features. Compute happens on a node where data is stored, it reduces data which needs to be shuffled over the network. Since every commodity machine has some basic compute power, you do not need specialized hardware and it brings the cost to a fraction More
For Spark 1.3 onwards, JdbcRDD is not recommended as DataFrames have support to load JDBC. Let us look at a simple example in this recipe. Using JdbcRDD with Spark is slightly confusing, so I thought about putting a simple use case to explain the functionality. Most probably you'll use it with spark-submit but I have put More