Apiphani Data Pipeline

Continuous access to trusted, role-specific data when and where needed

Industry-Leading Tools We Work With

What Can You Do with Apiphani’s Data Pipeline?

Tap into role-specific data when and where needed via data pipelines, which are end-to-end sequences of pre-defined and automated digital processes to continuously collect, modify, and deliver data. Take ownership of the three essential elements needed to become truly data-driven with the apiphani Data Pipeline.

These include:

A managed platform of modern data tools to build and support automated data pipelines
A business-first data-delivery approach aligned with your goals and objectives
A sustaining data Center of Excellence (CoE) to deliver, govern, and accelerate time-to-value

A Data Pipeline Platform that Saves Time and Delivers Value

Delivering reliable, easily accessible role-specific data. Most organizations spend 80% of their time gathering, cleansing, and preparing their data and only 20% in analysis. And they do it again and again, week after week, to produce the same reports with little time for analysis, insight, and innovation.

There is a better way.

Save time by automatically managing data quality and data complexity with apiphani’s Data Pipeline. It’s designed to provide reliable, streamlined, self-service data delivering value to your end users, data professionals, engineers, business managers, and executives.

A Business-First Approach to Continuous Data Delivery

Focused on delivering business value. The data once held in technology silos – trapped in whatever application created it – now becomes organized to deliver data value in the pipeline.

How? We organize and prioritize your data within data domains and production-grade data products defined by your leadership and data product owners, continuously refined and enhanced to align with your dynamic goals and objectives.

A Center of Excellence (CoE) for Now and the Future

Combine a secure data platform with complete managed services and a mature data strategy. Apiphani offers a complete data and analytics operating model of data domain leadership and data product delivery that includes business case, data product options value management as well as production grade data product delivery and adoption.

What does this mean for you? Accelerate data discovery and access as well as ensure data is secured, private, accurate, and usable.

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Client Testimonials

“The pipeline aggregates and organizes data so that engineers can do engineering work, not data work. Our aerospace and mechanical engineers don’t want to have to learn a new discipline to maintain the nuts and bolts of data pipelines, networks, IT and security. They are aerospace and mechanical engineers, not data engineers or IT professionals.”

Chief Data Scientist,

apiphani customer

211th

Fastest growing company in the U.S.

90%

Faster time-to-value

30%

Reduced cost of ownership

A Complete Solution for All Your Data Intelligence Roles

Incorporate the best of modern data and analytics principles, technology, and operating models to deliver role-specific data value with the apiphani Data Pipeline.

Our solution pulls together proven components widely recognized – both strategically and technically – as the underpinnings of successful data-driven enterprises.

The apiphani Data Pipeline solution will enable you to:

Access a secure data platform that is fully managed and continuously evolving, delivering high value-to-cost.
Organize and categorize system and department data from silos into value-driven data domains.
Realign shadow data and analytics resources with automated, enterprise self-service.
Define data product roadmaps based on options value analysis.
Create sustaining data and analytics leadership and center of excellence (COE) roles for domain operations and governance.

The data and analytics platform, combined with apiphani managed service, takes care of data quality and complexity and makes your data easily accessible and reliable across your organization.

Why Choose Apiphani?

Experts in data management and data engineering.

We’re not afraid to get data under our fingernails. Our people are experts at digging into the hidden and often complex flow of data throughout your organization – whether in the cloud, on-prem, or overseas. We can easily bring data engineering, data architecture, and data analysis roles to bear on your data problems.

Access the best people. Apiphani doesn’t use large pools of low-cost resources but rather relies on the unbeatable combination of talent and tech. You will have a named team that will be intimately familiar with your business.

Continuously optimize your solutions. Your business is constantly changing, as are your data sources and data requirements; it’s not a set it and forget it scenario.

Through apiphani’s managed services and elastic data and analytics model, apiphani can continue optimizing your data pipelines and ensure they evolve as your business evolves.

Nothing Succeeds Like Success

In four to six weeks, apiphani can deliver two to three data pipeline showcases for you.

Components of a Modern Data and Analytics Platform

The apiphani Data Pipeline is built around a reference architecture comprising all the components needed for a modern data and analytics platform. Supported by apiphani services to plan, implement, socialize and maintain them, the resulting data pipelines provide reliable, streamlined, self-service data that delivers value to end users, data professionals, engineers, business managers, and executives.

Establishing One Authoritative Source for Data

You can’t be data-driven unless you have trustworthy data. Business is increasingly data-driven, but many companies aren’t able to make that leap because they don’t have a single, cohesive, and verified source of data to drive their decisions – that “one source of truth.”

People are left on their own to find, clean, harmonize and join the data they need. The result is “shadow analytics,” where dozens of teams across the business are performing their own one-off data integration and analysis projects.

Eliminate shadow analytics. Shadow analytics waste time, lead to inconsistencies, and cause data-driven confusion. The apiphani Data Pipeline eliminates shadow analytics, creating a single, authoritative source of data available to people throughout your organization.

All the hard work of integrating and harmonizing the data from all the data silos is done within the Data Pipeline, in an automated, production-grade manner.

Accelerate data discovery and access. Our Data Pipeline will fundamentally change how your organization thinks about data, creating sustained Domain Leadership and a data and analytics Center of Excellence that drive and manage data and analytics operations and governance.

This will both accelerate data discovery and access as well as ensure your data is secured, private, accurate, and usable.

FAQ

Frequently Asked Questions

What makes apiphani's Data Pipeline and data and analytics services different from other providers?

We start with why data is central to value and follow up with exactly where and how data makes your organization stronger through insights, process optimization, and digital products.

Then we follow through with a comprehensive solution that covers the critical success factors for becoming data-driven:

A managed data platform, business driven data pipelines for self service, and a sustaining data and analytics operating model.

Is the apiphani Data Pipeline essentially a Data Mesh?

We take the best ideas and practices of Data Mesh, Data Fabric, Modern Data Platform, and Operating Model for organizing, discovering, securing, and governing your data and apply them to your specific needs.

Apiphani implements the data solution that’s right for your business.

How much of the Data Pipeline is apiphani’s responsibility versus our organization?

Apiphani takes responsibility and accountability for the Pipeline source connect, data product build, and data discovery and delivery.

Your organization sets priorities for what to build and establishes the Data Domain and Center of Excellence for discovery, usage, and governance using apiphani’s best practices model.

Apiphani typically focuses on building a minimum viable product (MVP) for data analysis and visualization to speed development and drive adoption, with branded design guidelines and best practices for self service development.

How much the MVP is iterated beyond that is up to you.

Why would I use the apiphani Data Pipeline versus build our own pipeline with our resources?

Building your own data platform and data pipelines requires highly specialized resources, takes time to develop, and is at risk of being suboptimal. Apiphani already has a high performance, cohesive team in place for this purpose.

Furthermore, we estimate that companies spend 20% more in year 1 building their first set of Data Products and then up to 40% more in subsequent years enhancing and maintaining data products.

It’s not just about getting the Data Pipeline built; it’s about maintaining it after launch to ensure it continues to be useful.

We also continuously improve and optimize our data platform with high value-to-cost components, including apiphani proprietary tools.

What is the best way to get started with apiphani to establish value and relationship?

We recommend taking three progressive steps, with each step providing clear objectives and outcomes to help evaluate how and whether to move to the next step:

1) Identify a data set that apiphani can put into the pipeline to quickly demonstrate the power and value of our services, at no cost to you.

2) Complete apiphani’s proprietary strategic data planning template so that we can together establish the best scope, objectives, and outcomes for the first engagement.

3) Identify and build two or three showcases that demonstrate value, create momentum, and build a foundation of reusable assets.

How does the apiphani address the difficult challenge of adoption?

First and foremost, adoption is not something that takes place only after the data products are built and ready for general use. Adoption must be part of the planning process from the beginning.

There are two parts to adoption that we address head on, from the start:

1) Redirecting shadow, siloed data and analytics capabilities to the apiphani Pipeline at every step.
2) Ensuring the data products are valuable, accessible, and – most importantly – designed as part of how the business operates.

The apiphani approach sees adoption as central to success and is built into what we do from the very start.

For example, ensure the Data Pipeline is on the C-Suite radar; onboard a topflight client business and technical team; provide active, clear roles for setting priorities; assign and train data product owners trained to think like product owners … and more.

What is a data pipeline?

Data pipelines are the connected modern data platform tools that move data from source systems at whatever pace is needed, automatically taking care of quality, commingling, analysis, and presentation for role-specific use by data consumers.

Data pipelines absorb data complexity so the data consumer has easy-to-understand, accessible, and reliable data.

Data pipelines transform raw data into actionable formats.

What are the challenges of implementing a Data Catalog?

A modern, third-generation data catalog is a cornerstone to successfully building and using data pipelines for a company. Everything that is built from the ground up is recorded and active in a third-generation data catalog.

From the consumer end, the catalog is the central tool for data discovery, understanding, and self-service.

Data catalog usage and adoption is a natural fallout when the catalog is built into both data product development and discovery processes.

Nothing succeeds like success.

Start small and build on your success.

Apiphani takes an iterative DataOps approach to data management and data engineering, starting small with showcase and proof-of-concept projects that reduce risk while increasing chances for an early win.

In four to six weeks, apiphani can deliver two to three data pipeline showcases for you.

The lessons learned and the reusable components created build a solid foundation for bigger data management and data analytics projects, and the early successes drive buy-in.