Data & Analytics Consultancy
Whether you are planning a new data initiative, revising your strategy, upgrading your architecture or simply want to improve outcomes, WHISHWORKS can help you gain clarity on how to best achieve your business and technology objectives.
With a proven discovery methodology, we help you to develop a broader scope for the initiative aligned to the business objectives, and to create a minimum viable product, an optimal solution and the shortest path to achieve your objectives.
Our Data & Analytics Consultants with work closely with you to:
- • Scope project requirements
- • Record data source systems, data integration and quality standards, data extraction methodologies and interfaces
- • Document user stories, architectural and non-functional requirements
- • Architect and implement a proof of concept
What we deliver
At WHISHWORKS, we begin with an initial project charter document to scope project requirements. Following this, we draft a project plan containing an initial schedule and an estimate of required effort for its implementation.
What follows is a high-level technical architecture document detailing recommendation for the architecture needed to support the proposed solution, and a high-level user story backlog describing an agreed understanding of requirements.
You are ready to solve your problem but not sure of what would be the right architecture, platform and tools to use.
To build a robust data management and analytics platform, the first and most important step is to have the right foundations, i.e, clear cut business requirements, meticulous understanding of workload, security and capacity. Secondly, the platform has to support data and analytics at scale. With our experience in building systems to handle petabytes of data and scale it to hundreds of nodes, you will be confident that the desired form and function are going to be met.
Our Data & Analytics Consultants work closely with you to:
- • Understand platform requirements, security, governance and information standards
- • Architect and design the platform based on your application, infrastructure and security requirements
- • Size and plan the platform capacity based on historical and future data volumes and workload
- • Design cluster security based on the core security standards and regulatory mandates
- • Platform installation with all required components as per the design
- • Implementation of required security configurations
- • Toolset installation to ensure constant monitoring and proactive alerting
What we deliver
Our experts will deliver a fully optimised and secured data management platform in line with your organisational standards. We also provide an operational guide and runbook with detailed information on day-to-day cluster management. And, to ensure your investment is sustainable, we offer knowledge transfer on cluster operations and management.
Data Integration Service
Connecting Applications, Data and Devices
Analysing data stored in silos has limited value. With an integrated data lake, you can unlock insights that would have otherwise been missed.
WHISHWORKS provides a unified solution for Data Integration: building, deploying, and managing real-time data-centric architectures in a big data environment.
Once the big data platform is setup, our data integration services aim to achieve multiple elements of integration, like batch and real-time data ingestion, from identified sources. The data transformation, data verification and quality activities ensure that information available is up to date, accurate, and consistent across systems.
Our Data & Analytics Consultants will work closely with your team to:
- • Scope data ingestion, transformation and quality management requirements
- • Record data source systems, data consuming platforms, data formats, data mappings, business rules, data transformation, data quality, data extraction methods and interfaces
- • Understand and document non-functional requirements like data volume and throughput.
- • Design key data processing frameworks/engines required for the implementation
- • Design detailed technical architecture and ensure adherence of end-to-end data lifecycle
- • Implement an end-to-end data integration solution
- • Perform unit, functional and performance testing to ensure business and non-functional requirements are met
Designed to give you the responsiveness and flexibility you need to turn data into actionable insights, our comprehensive managed services model lets you focus on your business strategy instead of worry about the technology infrastructure supporting it.
Data Platform Migration Services
The recent merger and acquisition announcements within the big data ecosystem brought a level of confusion and uncertainty. Many on-premise platform users are worried about the volatility of their platform, potential risks for their data and applications, as well as the suitability and viability of alternative courses of action. We can help.
Some of our customers are in the process of assessing or planning the migration of their on-premise big data platform to a cloud-native data platform. Our team of experienced architects and data engineers can guide you through the design and implementation of a complete migration (data, apps and workflows) from your on-premise platform to a cloud-native data platform (eg AWS, Google GCP, or MS Azure).
Our expert team of data consultants regularly conduct discovery sessions and more in-depth risk assessment engagements, to help companies choose the best option for their current technology stack and strategic roadmap.
Whether you decide to maintain, upgrade or migrate your on-premise data platform, our data engineers will align with your teams to accelerate timelines, eliminate risk, and minimise impact to your daily operations.
Lee Taaffe, Business Information Analyst at LGC | Data & Analytics
WHISHWORKS’ solution enabled us to achieve our business objectives and goals with increased service levels, demonstrating a high level of expertise by effectively implementing the project to the agreed timelines and going a level beyond what we thought was achievable.
Data & Analytics Solutions
Hortonworks Data Platform Support
Our Data & Analytics team will work with you to plan an approach and solution that best meets your needs. Together we will create a plan based on your technical environment, goals and projects.
If your Hortonworks platform is an earlier version than HDP 3.1, then you are probably assessing your options, as your existing platform technology stack may have already reached or will soon reach End of Life. At WHISHWORKS we have been working with all the major on-premise, hybrid and cloud Big Data platforms, including Hortonworks and Cloudera, and identified the following four paths dependent on your current HDP version and strategic roadmap.
Confluent & Apache Kafka Support
Our event streaming practice is underpinned by a team of expert senior Consultants with deep expertise in Confluent & Kafka deployments requiring high-availability, enterprise compliance, high-scalability, and industrial, robust operations.
Apache Spark Support
Apache Spark consulting, implementation, optimisation and support
Our Spark Specialism
Apache Spark is a fast and general engine for Big Data processing, with built-in modules for streaming, SQL, Machine Learning and graph processing. At WHISHWORKS we have worked extensively with Apache Spark in many Big Data projects:
• Implementation of robust production data pipelines at scale.
• Implementation of multiple “Spark and NiFi” based IoT pipelines.
• Numerous projects requiring Spark applications to perform efficiently on Yarn clusters.
• Introduction of SMACK (Spark, Mesos, Akka, Cassandra, and Kafka) stack into our Big Data roadmap.
• Development of reusable component registries, based on our extensive production experience to help reduce development time for building enterprise grade search solutions using Spark and Apache Solr, by almost 50%.
• Extensive experience into building and running production grade Data pipelines on cloud platforms like AWS and Azure.
• Multiple use cases involving streaming data processing, interactive analytics, batch processing and Machine Learning.