Apache Hadoop Сonsulting 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 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.
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 planning to implementation and managed services.
- Auditing the related existing IT environment.
- Analyzing potential Hadoop use cases.
- Conducting a feasibility study.
- Creating a business case, including ROI estimation.
- Designing the solution’s architecture.
- Planning the evolution of a Hadoop-based solution.
- Data modeling.
- Planning the migration of a data warehouse or the migration from disparate storage systems (if needed).
- Analyzing and designing security requirements.
- Creating a detailed deployment plan.
- Developing a disaster recovery plan.
Hadoop-based app implementation
- Designing and implementing a data transformation process.
- Developing data ingestion and data quality rules.
- Orchestrating workflows, creating custom algorithms for data processing and analysis, e.g., writing custom MapReduce code, Pig scripts, Hive queries, machine learning algorithms.
- Deploying, configuring, and integrating all architecture components of a big data solution.
Hadoop-based app QA and testing
- Designing an overall QA strategy and test plan for the entire Hadoop-based app and its analytical and operational parts.
- Designing test automation architecture.
- Choosing an optimal testing toolkit.
- Setting up and maintaining the test environment,
- Generating and managing test data.
- Developing, executing, and maintaining cases and scripts for functional, regression, integration, performance, and security testing.
- Development of new logic for data processing, data cleaning, and data transformation.
- 24×7 Hadoop-based application administration.
- Continuous performance monitoring.
- Ongoing optimization of applications, data, and IT infrastructure.
- Proactive and reactive support: problem resolution, root-cause analysis, and corrective actions.
- Security management.
- Backup and replication configuration.
- Planning and implementing Hadoop migration to the cloud (AWS, Azure).
- Planning and implementing migration 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 a beneficial, efficient, fast and secure big data solution. Leave the rest to ScienceSoft.
- In IT since 1989.
- Practical experience with 30+ industries, including BFSI, healthcare, retail, manufacturing, education, and telecoms.
- 700+ 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 Solution Partner.
- An AWS Select Tier Services Partner.
- ISO 9001 and ISO 27001-certified to ensure the mature quality management system and the security of the customers' data.
- ScienceSoft USA Corporation is listed among The Americas’ Fastest-Growing Companies 2022 by Financial Times.
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
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.
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
- 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
- We deployed an on-premises Hadoop lab for one of the largest US colleges that serves 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 team will be quick to get back with ideas, recommendations, and actions to discuss.