Petabyte scale analytics

❝ Excessive Growth Data is a top priority IT challenge for businesses today! We bring world-class expertise to help you get most of your Hadoop investment. ❞

How can we help you?

Scalable, secure and easily deployable solutions for Big data storage , processing  and building deep analytic applications.

With the increase in number of sensors per machine, we had gathered lot of data and it needed to be churned. Mactores with their analytics experts in IoT did it for us. They have an excellent approach to look at the problem and solve them progressively and effectively. We were able to explore unimaginable insights and gained a lot and lowered our operational costs as well.

Mark Phillips
Senior General Manager, Manufacturing Company

Digital data volumes are expected to double every two years for the foreseeable future. By 2020 there will be eight billion people on Earth, using 20 billion devices and communicating with 100 billion connected things. How can your company capture and manage data that’s important to you and drive  competitive insights in this information deluge?

We have some ideas. That’s why  world’s leading enterprises partner with Mactores to unlock the business value of their Big Data.  These companies know that the right data strategy can improve efficiency, attract customers and boost revenue.

We focus on  delivering actionable intelligence to the right people at the right time. It’s about accessing, analysing, and interpreting your most relevant data – then putting it to work

Be smart about your big data strategy at every stage of your journey. Lean on our experienced experts to help you build real-world Hadoop solutions with leading industry technologies

Usecase | Retail Analytics

Our customer – A multinational retail giant based in America collects 2.5 petabytes of unstructured data from 1 million customers every Day.We help them  manage, analyse and mine petabytes of their data to find out what is important and map it to drive effective revenue optimization strategies.

  • Data growth in PB

The retail giant made a move from 10 node hadoop cluster to a 250 node Hadoop cluster in 2012. The main objective of migrating the Hadoop clusters was to combine 10 different websites into a single website so that all the unstructured data generated is collected into a new hadoop cluster.

Since then, the Retail giant has been speeding along big data analysis to provide best-in-class e-commerce technologies with a motive to deliver pre-eminent customer experience. The Bar chart demonstrates the data explosion experienced by the Retail giant across 5 years. Data has grown in 10x magnitude

60+
Models Process

50,000
Orders/Hour

90
New data points/Month

Enterprise Solutions

Manage your data

We offer strategic options for organizations to engage with our team and quickly leverage expert resources to rapidly accelerate the analytical value of your data.

Data management

Store and process vast quantities of data in a storage layer that scales linearly.

Data Governance & Integration

Quickly and easily load data, and manage according to policy.

Data access

Interact with your data in a wide variety of ways – from batch to real-time.

Security

Address requirements of authentication, authorization, accounting and data protection.

Optimize your data

Design, build the most optimal data flow: from integrating data sources and implement big data applications on Apache Hadoop with the latest open source tools.

Application development

We help you design, build and optimize your big data applications on Apache Hadoop with the latest open source tools.

Solution design

Designing and implementing comprehensive solutions including – hardware infrastructure, data sources, ecosystem software and operation considerations for optimum performance within your environment.

ETL

ETL plan includes identifying multiple data sources and file formats, transforming and loading them into data structures best suited for your needs.

Data aggregation

Data aggregation to quickly and accurately consolidate and fuse data from various sources.

Insights for smarter decisions

Assess your business needs, define the business case, and recommend the suitable machine learning methods. Get new insights to make confident decisions in minutes.

Use case discovery

Understand business priorities and data sources available for analytics and identify & roadmap for big data development and training.

Statistical method

Develop right algorithm and statistical model to meet your speed, reliability and maintenance goals.

Data modelling

Transform and structure raw data to create a custom data model for your business needs.

Machine learning

Assess your business needs, define the business case, and recommend the appropriate machine learning methods.

Technology expertise

MAP R
MAP R
Azure HDInsight
Azure HDInsight
Amazon EMR
Amazon EMR
Apache Spark
Apache Spark

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