Enlighten your Big Data with Apache Spark™?

Hadoop => Most cost effective and scalable system to store Big Data.
Spark => Simple unified platform for all compute needs for Big Data.
Hadoop + Spark => Complete Business Insights

  • Storage

  • Compute

  • Insights

Have you formed your Data Lake yet?

How sick are you of your data sitting in silos?
How cumbersome is it to get even simple piece of information from other departments?

Big Data Lake at the cost of EDW bucket

Hadoop and other Big Data technologies let you collect all the data in one system, at a fraction of the cost of traditional EDW systems.

No need to think about what data to save and what to throw away. No need to archive data in tape drives.

The benefit: “Get every ounce of Insight from data”

Our expertise in Big Data systems enable us to advise you about the right strategy to create and maintain Big Data Lake.

We have right tools and expertise to process your Big Data once lake is formed.

Spark – The Unified Platform for Big Data Apps

Spark provides a single platform which has libraries for all of your Big Data compute needs.

No disparate compute tools, just libraries

Over the years, multiple technologies have emerged to cater to different big data compute needs like Storm (Streaming), MapReduce, Hive(SQL like interface), Pig (high-level scripting), Mahout(Machine Learning) etc.

These technologies came with their own set of features, as well as Challenges. Spark completely changed the game. It caters to different compute needs by simply providing right libraries. Following are the libraries which come with Spark bundled as standard:

  • Spark SQL
  • Spark Streaming
  • MLLib (Machine Learning Library)
  • GraphX

Our team of experts can help you process data using Spark and it’s libraries, so that you can derive actionable insights that improve your business.

Eureka or Enlightenment phase

The promise of Big Data lies in being able to make more informed decisions – to increase sales, decrease costs, or execute your mission more efficiently. Our Big Data Analytics provide useful insights that until now could only be suggested by sampling, or were completely invisible.

Visualize your way to insights

The insights you need are buried in huge amounts of fast-moving data in a variety of data types. Looking at raw data is not only inefficient but also boring. Humans believe in power of stories and the moment you start visualizing data, it starts telling stories.

We have expertise in all industry leading visualization tools like Tableau, Datameer and Qlikview. We can also help you create custom dashboards which provides tailor made visualization interface.

Here are some examples of custom visualization.

Ask about our free Big Data POC at no cost or obligation.

From Our Blog

SparkSql: LeftOuter Join with DSL

SparkSQL is great at executing SQL but sometimes you want to stick to RDD level. There comes the role of DSL. Sometimes how exactly to use Spark with DSL becomes confusing. This recipe is an attempt to reduce that. Let's get done with pleasantries first i.e. loading SQLContext and imports scala>val sqlContext = new org.apache.spark.sql.SQLContext(sc) scala>import sqlContext._ scala>import org.apache.spark.sql.catalyst.plans._ We are going to ... More

Demystifying compression

Compression has an important role to play in big data technologies. It makes both storage and transport of data more efficient. Why are so many compression formats then and what are the things we have to balance while making a decision which compression format is better. When data is compressed, it becomes smaller so both disk I/O and network I/O ... More

MapReduce is dead, Long Live MapReduce!

MapReduce has an interesting legacy in Big Data space. It started with MapReduce paper, Google published back in 2004. When Hadoop was created, it had two parts, HDFS for Storage and MapReduce for compute. 10 years later, MapReduce is dead. Few companies still have skeletons hanging but mostly it's dead. But the physical death of MapReduce does not reduce it's ... More

Past, Present and the Future of Big Data

InfoObjects has focused on Big Data space for at least two years. Technology has progressed a lot during this time but technology adoption by customers is a different story. Customers were sitting on fence as they were not sure which technology flavor to adopt. Every software vendor was touting their own horn, including open-source software vendors (oxymoron :) ). Customers ... More

PR Newswire Article on InfoObjects' Cloud-based LBA Engine

InfoObjects' Cloud-based LBA Engine Exceeds 100 Million Geofence Assessments in Large-scale Mobile Advertising Campaign SANTA CLARA, Calif., June 26, 2014 /PRNewswire/ -- InfoObjects of Santa Clara, California, announced a major performance milestone for location-based advertising (LBA) technology. In a recent customer engagement campaign conducted for Hipcricket, a mobile marketing and advertising technology company located in Bellevue, Washington, over 100 million geofence ... More

Dust is settling down in Big Data space

Big Data space is interesting in many ways. Big Data is changing the landscape, but then landscape also is changing Big Data. In this blog, I will look at them from different angles. Gartner Big Data Hype Curve Below is Gartner's Hype cycle for emerging technologies According to this graph, Big Data is about to reach the peak of hype cycle. This data ... More