Data Collaboration

It's time to re-set your expectations

Within an enterprise data architecture, what's in control? Is it the applications or the data? For most, it's the applications. But applications are useless without data. As a result data becomes the servant to the applications. As more applications are built, more data copies and more silos are created, leading to a never ending cycle of architectural complexity.

Moving towards collapse two steps at a time

An application led approach may seem like small steps forward for the business but in reality it's actually moving it closer and closer to collapse by complexity. Ultimately creating an unruly ecosystem of disparate applications tethered to disparate databases and repositories.

Getting out of this cycle requires thinking “differently”. It requires actually changing the way you change. It's realizing that a little better is not good enough and that traditional approaches should not be directing solution design.

An example to ponder. Automobile manufacturers. Some think they are moving two steps forward by making combustion engines more fuel efficient. This "progress" doesn't solve the larger problems of cost, reliability and the reliance on fossil fuels. As a result, more versions of better will continue to be needed, little by little, over and over, stuck in the cycle of the traditional.

Some are taking a completely different approach. Electricity. Solving the problems of efficiency, emissions and fuel source in one fell swoop. This approach to change has also created brand new opportunities for growth, expansion and simplification. Why? Because these companies changed the way they thought about a single problem and as a result rid themselves of ALL the problems. They now live and operate in a world where old problems are irrelevant.

Let’s first start off looking at other common data management models and solutions on the market today. Data warehouses, data visualization, data lakes, data mesh and data fabric. All good models/solutions, yet all still act as a means to move only a few steps forward.

Why? Because with all of these solutions data remains under lock and key. It’s stuck in a world where applications are still in control of the data. As a result, all of these models require heavy integrations and there remains many different versions of data, all housed in silo’s. All this splintered data is difficult to govern. Access to the people who need the data to make good business decisions can often be completely blocked. There is nothing really "different" about any these approaches.

Data Collaboration is different.

It gets the enterprise into a new universe by first doing one thing completely different.

It integrates data without integration

A Data Collaboration Network liberates enterprise data and evolves it into a federated, fully collaborative network. Data being free, puts it in control. The paradigm of application control is flipped on its head and a new universe of how data interacts in the enterprise is created.

What is data collaboration? It entails the collection, exchange and use of data from different origins within an organization. This interaction creates data products with data owners acting as experts for their specific data domains. The interaction of these various data set domains also results in dramatically informed insights that are solely driven by the interactions of the data itself.

Cinchy's Data Collaboration Platform enables an enterprise organization to create data in an productized manner, one in which data structures can be defined independent of any one business solution planning on leveraging that data. The way the data is modeled is in a manner that is conducive to the business and how the business thinks about its information usage.

The Data Collaboration Platform in the enterprise can be generalized into 3 components:

Data Liberation

Application owners can make data available to access and change via the dataset network with real-time 2-way synchronization. Bridging the gap between the legacy world and the new way the business can now manage their data. Bi-directional connectivity allows data to freely flow in and out of the dataset network as needed.

Data Productization

The dataset network is composed of individual domains of interconnected data sets or data products. This environment provides the capability of being able to model, protect and control data in a manner that is democratized, where many different teams can work in a completely federated way, building out this network of information. Data product owners can create and manage data products with granular access/control policies enabling real-time data collaboration.

Data Collaboration

Project teams can use data products to access and change data to meet their project requirements without dependence on individual apps/teams. This allows the enterprise to interact with the data and further build additional application-based capabilities as needed. This is accompanied by a pre-built data browser as the main user interface, allowing users to explore, access, view, and change information subject to their level of access.

Platform Capability

Benefit for Documents

Benefit for Data

Metadata Plasticity

Links don’t break when files are renamed or moved

Queries/Links/APIs don’t break when columns are renamed or dropped

Universal Governance & Controls

Access to files/folders can be granted and revoked by owners at any time

Access to rows/columns/cells can be granted and revoked by owners at any time

Version Control & Lineage

Files and metadata changes are versioned & can be diff’ed and rolled back

Data and metadata changes are versioned & can be diff’ed and rolled back

UI for Data Collaboration

Real-time collaboration UI for users to search using metadata and access/create/add files

Real-time collaboration UI for users to search using metadata and access/create/add data

API for Data Collaboration

Real-time collaboration API for appsto discover/access/modify/add files

Real-time collaboration APIs for apps to discover/access/modify/add data

“Data Collaboration is a bold reimagining of the relationship between data and applications, where applications run on a shared data repository rather than individual dedicated databases, thus eliminating the need for data integration and preventing data duplication. So many of the tools we use today focus on bringing data together from multiple applications, but, with Data Collaboration, the data is never separated to begin with.”

Eckerson Group

Survival Guide - Integration is Obsolete

One Pager

Integration is Obsolete: A Survival Guide

Analyst Report

Applications, Silos and Complexity, Oh My!

Analyst Report

Data Collaboration

It's time to re-set your expectations

Moving towards collapse two steps at a time

Change the way you change

Different, not better is the way forward

What exactly does different mean in this context?

Data Collaboration is different.

It gets the enterprise into a new universe by first doing one thing completely different.

It integrates data without integration

How does data collaboration work in the enterprise?

Data Liberation

Data Productization

Data Collaboration

This entire package of these capabilities forms the solution known as the Data Collaboration Platform.

Collaboration requires an enabling platform

Dig deeper into data collaboration

Integration is Obsolete: A Survival Guide

Applications, Silos and Complexity, Oh My!

Enabling Data Mesh Principles and a Data Fabric Foundation

See Data Collaboration in action!