Data Services

DATA
ENGINEERING

Put enterprise data to work for the business

Rappino provides end-to-end Data Lifecycle Management tailored to evolving data consumption patterns—ensuring consistent accessibility, quality, and governance at every stage.

The Challenge

Businesses need an
efficient and agile
way to source and
consume data

Enterprises today have access to enormous amounts of data from multi-cloud infrastructures. However, their ability to put that data to work is limited due to increasing complexity, poor data management and ill-equipped infrastructure and tools. Overcoming these obstacles requires several things:

Being able to turn a fast-growing pool of enterprise data into actionable intelligence.
A trustworthy data foundation and enabling analytics supported by insights from a wide range of data sources.
Proper data preparation that allows insights from raw data — for all types of analytics. Insights that are available in context-specific patterns for interactive visualizations, and predictive and prescriptive analytics.</li

What we do

WE OFFER DATA ENGINEERING
SERVICES TO ACCELERATE
DIGITAL EVOLUTION

Rappino helps enterprises solve their data challenges, improve end-user satisfaction, and help guide business strategies based on intelligent insights. Our data engineering teams analyze structured, semi-structured, and unstructured data with the right technology, processing tools, and approach. In addition, we provide complete data lifecycle management services, replacing costly and siloed in-house data infrastructure and turning big data pipelines into robust systems prepared for agile business analytics.

Our Offerings

List of our Data Engineering Services

DATA COLLECTION & SUMMARIZATION

Extraction of structured, unstructured data coming from streaming and batch sources and refining/cleansing data to make it available on legacy database or cloud systems, to data scientists and business users for exploration and analysis.

Data Storage & ELT / ETL

Extracting, processing, transforming, and loading data techniques into various relational, non-relational, NoSQL, big data systems and/or cloud storages, depending on data availability, volume, velocity, and type of data.

DATA COLLECTION & SUMMARIZATION

An efficient and smart approach for migrating business data to / from on-prem legacy systems into cloud storage infrastructure or new target platforms.

Data Pipelines

Building production-grade repeatable and independent data workflow pipelines to move, transform and store data.

Using various legacy, Big Data and / or cloud orchestration and data management pipeline tools and techniques like DF, Databricks, Synapse, Informatica, and others, to process data in batch and real time.

Continuous Integration & Deployment

Expertise in legacy and cloud-based deployment services for developing efficient production build and release pipelines based on infrastructure-as-code artifacts, reference / application data, database objects (schema definitions, functions, stored procedures, etc.), data pipeline definitions and data validation and transformation logics.

DATA COLLECTION & SUMMARIZATION

Expertise in providing data insights and intelligence on stewardship, compliance and regulatory drivers for client consideration and decision making.

Data Quality

Automated data quality solutions for critical tasks, including correction, enrichment, standardization, and de-duplication.

THE OUTCOMES WE DELIVER

Monetize and
maximize the value
of data

Benifits of our Data Engineering Services

Faster time-to-value

With accelerators, frameworks, and proven services without compromising quality

Improved Operational Efficiency

Leveraging operational data to improve efficiency; developing ML/AI use cases to improve sales and operations; access distributor data to get better supply chain visibility, identify gaps, and improve replenishment rates

New Customer & Market Insights

Access retail data and integrate market research to gain new insights into consumer behavior and inventory levels

New Customer & Market Insights

Access retail data and integrate market research to gain new insights into consumer behavior and inventory levels

Enhanced Compliance

Integrate regulatory and market data to align sales and distribution

Increased Sales

Leverage online/e-commerce data to fuel sales initiatives

Our methodology
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how we do it

Our process

Rappino uses a consultative approach that combines data engineering, cloud, data privacy, and compliance expertise with proprietary frameworks and maturity models to construct a modern data ecosystem. In addition, our flexible resourcing model allows for the rapid scaling of teams through a pod or virtual pod-based approach.

We also leverage pre-engineered accelerators and digital assets across all
of our Data Services to accelerate the data transformation journey. These include:

M4 Data Strategy Roadmap

A proprietary execution framework for analytics engagements. M4 provides a proven strategy
and predictable steps for data modernization. It helps map use cases to modernize
architecture and migrate to the cloud while giving all stakeholders a clear view of expectations.

map

Map business OKRs and IT goals to build a comprehensive view of strategic intent for the program

Map current state challenges with strategic goals to showcase critical milestones (Quarterly view)

Map milestones (Quarterly) with specific data assets, data products and capabilities delivered

modernize

Modernize hosting platform, foundation, data products like DQ engine, catalog, lineage, discovery, virtualization, etc.

Modernize data architecture and deliver data models for optimized semantic layer, integrated key management process, data pipeline

Modernize information consumption capabilities

migrate

Migrate legacy data assets onto target state platform as per reference architecture

monitize

Monetize data assets by empowering business users through governed, self-service capabilities to deliver faster insights

A cloud-native, advanced data analytics framework that provides intuitive, flexible self-service access to BI, visualization and analytics insights to help business leaders and analysts make smarter, faster decisions. iC4 provides best-in-class tools for the four foundational principals of information management — Curate, Catalog, Context, and Consume. This stepwise approach and architecture allow organizations to capitalize on the benefits of analytics applications without having to build and maintain a huge data warehouse, visualization capabilities, and reporting platforms.

Data Dip

This framework solves challenges associated with data pipeline validations. It is distributed in the form of deployable code framework which seamlessly integrates with existing AWS data ecosystems.

Our expertise

DATA ENGINEERING AND ANALYTICS TOOLS

Rappino has experience with the leading cloud and analytics tools, and platforms. We take an agnostic and unbiased approach with the goal of selecting the right tools for the organization and environment. We can help you take full advantage of these tools and platforms to maximize your ROI with them.

key
partnerships

We can help you accelerate your time-to-market and increase agility with our comprehensive suite of AWS offerings. Industry-best standards and AWS-guided design patterns drive our AWS cloud solutions. In addition, we adhere to a disciplined continuous review process with experienced and talented AWS-Certified resources.

learn more

Our partnership with Azure helps organizations move to cloud at speed, increasing application availability, technical flexibility, and security improvements.

Monetize your data with the help of Rappino end-to-end migration and implementation services for Snowflake Data Cloud. Rappino offers end-to-end migration and implementation services for Snowflake Data Cloud, including design, data preparation, re-platforming, and performance optimization.

learn more

why Rappino

EXPERTISE IN DESIGNING & EXECUTING DATA STRATEGY IN DATA-INTENSIVE ENVIRONMENTS

Rappino has expertise designing and implementing data strategies across the functional, governance, talent, and engineering aspects of businesses. Our teams have worked for Wall St. banks (some of the most challenging and data-intensive environments) and helped chart the course of their data journey.

proven
ACCELERATORS FOR
FASTER TIME-TO-VALUE

Rappino combines Human intelligence (SMEs and Data Architects) with cloud-native accelerators to help enterprises realize their true business potential.

READY-TO-CONFIGURE DATA
MODELS, FRAMEWORKS, &
MICRO-SERVICES

We provide transformative insights to customers without compromising on quality.

FAQ’s – Data Strategy

1. What is a data strategy?

A data strategy is a comprehensive plan that outlines how an organization will collect, manage, analyze, and utilize data to achieve its business goals. It is crucial because it ensures that data is leveraged effectively to drive decision-making, optimize operations, and gain a competitive edge. Without a well-defined data strategy, organizations risk making decisions based on incomplete or inaccurate information, leading to missed opportunities and inefficiencies.

2. How do data strategy services benefit businesses?

Data strategy services provide businesses with expert guidance and support in developing and implementing a robust data strategy. These services help organizations identify key data sources, define data governance frameworks, and establish a data-driven culture. By leveraging data strategy services, businesses can unlock the full potential of their data, enabling them to make informed decisions, enhance customer experiences, and drive innovation.

3. What are the essential components of a successful data strategy roadmap?

A successful data strategy roadmap typically includes several key components: data governance, data architecture, data quality management, data integration, and analytics capabilities. It outlines the steps required to achieve short-term and long-term data objectives, aligning data initiatives with business goals. The roadmap also identifies the tools, technologies, and processes needed to support data-driven decision-making and ensures that data is consistently managed and utilized across the organization.

4. What are the best practices for developing a data strategy?

Developing a data strategy involves several best practices: aligning the strategy with business goals, establishing clear data governance policies, ensuring data quality and integrity, and fostering a data-driven culture. It’s also important to create a flexible data architecture that can scale with your organization’s needs and to invest in analytics tools that provide actionable insights. Regularly reviewing and updating the data strategy roadmap is essential to adapt to evolving business requirements and technological advancements.

5. How does a data strategy differ from a data management plan?

A data strategy is a broader, overarching plan that outlines how an organization will use data to achieve its business objectives, while a data management plan focuses on the specific processes and practices for handling data on a day-to-day basis. The data strategy sets the vision and direction for data utilization, including governance, analytics, and innovation, whereas the data management plan details the operational aspects of collecting, storing, and securing data.

What Our Customers Say

Through our partnership with Apexon, we have been able to achieve many goals. One is to get our platform built with speed by helping our engineering teams and then we have also achieved our infrastructure goals of ISO certifications. Apexon team is helping us deploy the platform even faster from two or three times per week to five or six times a week.

Mark Fleishman

VP of Infrastructure and Operations, Paige

Their(Apexon) attention to detail and continued focus on CD Valet has kind of proved that we made the right decision and we have expanded from one team to multiple teams. We are surveying about 31,000 CD rates on a weekly basis and Apexon plays a very important part in that process.

Data Services

DATA ENGINEERING

The Challenge

Businesses need an efficient and agile way to source and consume data

What we do

WE OFFER DATA ENGINEERING SERVICES TO ACCELERATE DIGITAL EVOLUTION

Our Offerings

List of our Data Engineering Services

DATA COLLECTION & SUMMARIZATION

Data Storage & ELT / ETL

DATA COLLECTION & SUMMARIZATION

Data Pipelines

Continuous Integration & Deployment

DATA COLLECTION & SUMMARIZATION

Data Quality

THE OUTCOMES WE DELIVER

Monetize and maximize the value of data

Faster time-to-value

Improved Operational Efficiency

New Customer & Market Insights

New Customer & Market Insights

Enhanced Compliance

Increased Sales

Our process

M4 Data Strategy Roadmap

map

modernize

migrate

monitize

Data Dip

Our expertise

DATA ENGINEERING AND ANALYTICS TOOLS

keypartnerships

why Rappino

EXPERTISE IN DESIGNING & EXECUTING DATA STRATEGY IN DATA-INTENSIVE ENVIRONMENTS

provenACCELERATORS FOR FASTER TIME-TO-VALUE

READY-TO-CONFIGURE DATA MODELS, FRAMEWORKS, & MICRO-SERVICES

FAQ’s – Data Strategy

What Our Customers Say

Mark Fleishman

Yatin Pradhan

Meet Our Experts

Kumar Roy

Chethan Laxman

RELATED OFFERINGS

Knowledge Hub

Address

Email

Phone Number

All Quick Links

DATA
ENGINEERING

Businesses need an
efficient and agile
way to source and
consume data

WE OFFER DATA ENGINEERING
SERVICES TO ACCELERATE
DIGITAL EVOLUTION

Monetize and
maximize the value
of data

key
partnerships

proven
ACCELERATORS FOR
FASTER TIME-TO-VALUE

READY-TO-CONFIGURE DATA
MODELS, FRAMEWORKS, &
MICRO-SERVICES