YOUR RECIPE TO BUILD REPEATABLE DATA PRODUCTS
In this blog, we’ll walk you through our groundbreaking concept to deliver best-in-class data products for business consumption and explain why we believe Modak’s Data Engineering Studio ™ will revolutionize data engineering forever.
For the first time, Modak's Data Engineering Studio ™ has captured the learnings from decades of experience, hundreds of projects and thousands of data pipelines and packaged these into one cohesive methodology., providing enterprise data teams a brand-new set of pre-packaged, tested, and proven methodologies, tools, training, integrations, and practices that enable Enterprises to build continuous data flywheels.
Modak’s Data Engineering Studio™ bridges the gap between analytical, business, IT infrastructure, data platform and data processing teams build on industry standard Scaled Agile Framework (SAFe™). Accelerating the delivery of federated data domain for consumption by analytical teams and AI. Furthermore, the studio approach ensures continuous delivery of data products as a service, monitoring, and skilled managed service teams to institutionalize a DataOps culture.
With Modak Data Engineering Studio™ enterprises can easily implement Modern Data Platforms that are innovation ready and support large digital transformation efforts. Modak provides the best-in-class templates, tools, processes, expertise, and data domain knowledge to enable data orchestration across cloud provider. The capabilities provided by Modak’s Data Engineering Studio™ are enabled by Modak Nabu ™, an intelligent data orchestration platform.
Let’s take a look at the deliverables of Modak’s Data Engineering Studio:
Integrated Pod Structure
Modak Integrated POD is a fusion of self-organized, cross-functional, disciplinary team comprising Data Engineers, Data Ops Engineers, SRE Engineers, Technical Leads, SMEs and DB Administrators, with diverse extensive experience in data software tools such as Kafka, Spark, and Cloud technologies (Microsoft Azure, AWS, and Google). Modak works with the Scaled Agile Framework® (SAFe) for software development and delivery.
Cloud 3.0: Multi- Hybrid Cloud Strategy
Modak works with big data cloud software providers, cloud configuration tools to install, configure and manage cloud provider products such as Microsoft Azure Data Lake, Microsoft Synapse, AWS, GCP, etc. Data can be moved to a single cloud platform, or multi-cloud platform based on landing areas such as AWS S3 or MS Azure ADSL or Google BigTable.
Modak Nabu™ provides workspaces where collaboration with business domain experts, data engineers and data stewards are enabled through low-code UI to create data domain products for consumption. Modak teams design, develop, and test automated data ingestion and curation pipelines from on-prem data sources to the Cloud.
Managed DataOps team comprises highly experienced and certified team of support and management of MS Azure, AWS, GCP data platforms. They monitor and provide all the cloud platforms periodically for alerts and warnings, troubleshoot any identified issue as per agreed SLA, and SLO’s and optimizing performance and cost. Within this function, Site Reliability Engineering enables monitoring cloud data platform uptime, performance, and other components that include dependency with other software components.
Deep Data Domain Knowledge
Modak has extensive domain and technical experience converting legacy data into appropriate formats, with Modak Nabu’s Data Spiders and BOTs capabilities, our data teams can rapidly create an active metadata driven data fabric, with over 15k pre-built transformation functions. Deep understanding of ingestion and processing data sets along with years of experience working with complex data formats, types, transformations, and building large-scale, including complex R&D genome data assets.
DIGITAL ACCELERATORS FOR A MODERN DATA PLATFORM
A Modern Data Platform is a new architectural pattern for data management. Modern Data Platform provides an automated data infrastructure that continuously feeds analytical models and AI algorithms, through standardized data products that evolve as more data is fed into them – hence the “data flywheel” analogy. One of the tenets of a modern data platform is a focus on the entire source data landscape and tackling multiple use cases versus the traditional approach of limiting to project-level or functional level requirements.
Modak Nabu™ allows enterprises to automate data ingestion, profiling, and curation tasks. Modak Nabu™ joins multiple heterogeneous datasets and creates a data fabric which enables data lake creation. Once data has been profiled, Modak Nabu™ allows domain driven data products to be curated through data mesh framework build on Workspaces. We believe that data fabric and mesh should operate together and not as independent approaches.
Let’s understand the core elements of a modern data platform:
a) Data Fabric
The data fabric provides the data services from the source data through to the delivery of data products, aligning well with the first and second elements of the modern data platform architecture. Modak Nabu’s Data Fabric provides a “net” that is cast to stitch together multiple heterogeneous data sources and types, through automated data pipelines that proliferate an active metadata repository.
b) Data Lake
A data lake is a central repository that enables you to store all of your structured and unstructured data at any scale. Modak Nabu’s automated data pipelines accelerate the data ingestion process and reduce the time required for data lake creation.
c) Data Mesh
Data mesh aims to connects the two planes of operational and analytical data sets and deliver business-owned data products with a lifecycle (just as software) and consumed through APIs. Modak Nabu delivers domain driven data products with data-based principles. These data products are consumed by data and business users.