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Hadoop Consulting and Support Services

On a Mission to Create High-Performing and Scalable Solutions for Big Data Storage and Processing

In big data since 2013 and in data analytics since 1989, ScienceSoft designs, develops, supports, and evolves big data solutions based on the technologies of the Apache Hadoop ecosystem.

Hadoop Services - ScienceSoft
Hadoop Services - ScienceSoft

Hadoop services help businesses efficiently build big data solutions based on HDFS, MapReduce, and YARN, as well as other Apache projects, custom and commercial tools. Such solutions enable big data ingestion, storage, querying, indexing, transfer, streaming, and analysis.

All the Help You Need with Hadoop Projects

ScienceSoft offers all kinds of services to help mid-sized and large businesses build tailored operational and analytical big data systems. We cover everything — from strategy and project planning to implementation and managed services.

Hadoop consulting

Hadoop consulting is a way to get expert advice and guidance on how to effectively implement, migrate, and configure Hadoop. ScienceSoft's Hadoop consultants can:

  • Audit the existing IT environment.
  • Analyze potential Hadoop use cases.
  • Conduct a feasibility study.
  • Create a business case, including ROI estimation.
  • Design/redesign the architecture of a Hadoop-powered solution.
  • Improve performance and security.
  • Conduct Hadoop-related training for your in-house teams.
  • Develop a disaster recovery plan, and more.

Hadoop development services

Hadoop development services refer to creating Hadoop-powered solutions tailored to an organization's specific needs. These services include:

  • Developing data ingestion and data quality rules.
  • Creating custom algorithms for data processing and analysis, such as writing custom MapReduce code, Pig scripts, Hive queries, and machine learning algorithms.
  • Deploying, configuring, and integrating all architecture components of a big data solution.

QA and testing of Hadoop-based apps

To ensure the quality of a Hadoop-based application and its analytical and operational components, a comprehensive QA strategy and test plan must be designed and executed. This involves:

  • Creating a test automation architecture.
  • Selecting the most suitable testing toolkit.
  • Creating and maintaining a test environment.
  • Generating and managing test data.
  • Developing, executing, and maintaining test cases and scripts for functional, regression, integration, performance, and security testing.

Hadoop support

Hadoop support is a way to ensure the smooth and efficient operation of Hadoop-based apps. These services may involve:

  • Problem resolution, root-cause analysis, and corrective actions.
  • Bug fixing.
  • Upgrades.
  • Backups and disaster recovery.
  • Continuous performance and security monitoring and management.
  • Development of new logic for data processing, cleaning, and transformation.

Support services can be provided on an ongoing basis or as needed, depending on the organization's requirements.

Hadoop migration

Hadoop migration is the process of moving data and applications from one Hadoop environment to another. This can involve:

  • Planning and implementing migration from an on-premises Hadoop cluster to a cloud-based Hadoop environment, e.g., on AWS, Azure.
  • Migrating from one Hadoop distribution to another, e.g., from a commercial Hadoop distribution (e.g., Cloudera Data Platform, Hortonworks Data Platform) to vanilla Hadoop.

Let ScienceSoft Show You the Best of Hadoop

Enjoy the benefits of efficient, fast and secure data processing and analytics on Hadoop. Leave the rest to ScienceSoft.

Contact the team

Why Choose ScienceSoft for Your Hadoop Projects

  • In IT since 1989.
  • Practical experience with 30+ industries, including BFSI, healthcare, retail, manufacturing, education, and telecoms.
  • 750+ experts on board, including IT consultants, big data architects, Hadoop developers, Java, .NET, Python developers, DataOps engineers, and more.
  • Established Agile and DevOps practices.
  • A Microsoft partner since 2008.
  • An AWS Select Tier Services Partner.
  • Quality-first approach based on a mature ISO 9001-certified quality management system.
  • Customers’ data security ensured by our ISO 27001-certified information security management system that bases on unfailing practices and policies, advanced techs, and security-savvy IT experts.

  • For the second straight year, ScienceSoft USA Corporation is listed among The Americas’ Fastest-Growing Companies by the Financial Times.

Join Our Happy Clients

We needed a proficient big data consultancy to deploy a Hadoop lab for us and to support us on the way to its successful and fast adoption. ScienceSoft's team proved their mastery in a vast range of big data technologies we required: Hadoop Distributed File System, Hadoop MapReduce, Apache Hive, Apache Ambari, Apache Oozie, Apache Spark, Apache ZooKeeper are just a couple of names. ScienceSoft's team also showed themselves great consultants. Special thanks for supporting us during the transition period. Whenever a question arose, we got it answered almost instantly.

We would certainly recommend ScienceSoft as a highly competent and reliable partner.

Kaiyang Liang Ph.D., Professor, Miami Dade College

Hadoop-Related Technologies We Use

Head of Data Analytics at ScienceSoft

We typically recommend Hadoop deployment in the cloud for applications requiring elasticity and potential changes in computing resource consumption. On-premises deployment may be a viable option for projects with strict security requirements, a static scope, and a willingness to invest in hardware, office space, and DevOps team ramp-up.

FAQ

To build a Hadoop-based application, should we simply install and tune all the required frameworks?

Building a Hadoop-based solution is a lot more than that. 95% of big data implementation is custom development.

It looks like a huge, long-lasting project that costs a fortune. How do you manage investment risks?

We always conduct a feasibility study, target positive financial outcomes, and deliver ROI estimates. We also ensure our clients start getting value early and proceed iteratively.

Can we use Hadoop for real-time data processing?

Yes, absolutely. For that, ScienceSoft can leverage such techs as Apache Storm, Apache Spark Streaming, Apache Samza, and Apache Flume.

Our Featured Hadoop Projects

Big Data Solution for Advertising Channel Analysis

Big Data Implementation for Advertising Channel Analysis in 10+ Countries

  • We modernized an analytical system to track advertising channels in 10+ countries.
  • The new system enables a cross-analysis of ~30K attributes and builds intersection matrices allowing multi-angled analytics for different markets.
  • The new system is able to process queries up to 100 times faster than the outdated solution.
Collaboration Software MVP for an International Consulting Company

Collaboration Software MVP for an International Consulting Company

  • In 10 months, we built a complex MVP based on Delta Lake with a mechanism for multi-layered data storage.
  • The MVP enabled quick processing of heterogeneous data on the Customer’s projects from multiple sources and the possibility to track the record of the added, modified, and deleted data.
  • ScienceSoft ensured secure storage of voluminous client data, data archiving, and advanced data processing capabilities.
Hadoop Lab Deployment and Support

Hadoop Lab Deployment and Support

  • We deployed an on-premises Hadoop lab for one of the largest US colleges that serves as a valuable source of practical knowledge for the students.
  • Our consultants also conducted a number of remote training sessions, where we explained in detail how each component of the data platform should work, and prepared detailed guides explaining how to work with the lab.
  • Key technologies: Hadoop, Apache Hive, Apache Spark.

We Are Up for New Interesting Hadoop Projects!

Share your vision, scope, business challenges, anything — and our Hadoop experts will be quick to get back with ideas, recommendations, and actions to discuss.

Our Blog about Hadoop

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Hadoop Implementation

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Apache Cassandra vs. Hadoop Distributed File System: When Each is Better

Find out the key distinctions between Apache Cassandra and HDFS.

All about Data Analytics and Big Data