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Cultural Challenges to DataOps Success (1)

This is part 1 of a 4 part series on DataOps

What is DataOps?

DataOps is an emerging idea, with many perspectives.  For this post, I am using the following definition is from Hitachi-Vantara:

DataOps is enterprise data management for the AI era. Now you can seamlessly connect your data consumers and creators to rapidly find and use all the value in your data. Data operations is not a product, service or solution. It’s a methodology, a technological and cultural change to improve your organization’s use of data through better data quality, shorter cycle time and superior data management.

The most significant challenge to implement DataOps is going to be cultural, not technology.  The following protocols are suggested to address some of the main cultural barriers that exist. 

Tilting at Windmills

Data was never scarce. The means to access it, the ability to manipulate it and the capacity to store data were expensive, therefore controls were put in place to manage these expenditures.  Over time, IT departments assumed the role of guardians of the data and began to treat data as scarce.  To this day, the first response to any data request is “Why do you need it?”.  Management of the means – data access - became confused with management of the ends – the data.  (Someone said to me it’s like stating ocean water is scarce because you only have a dozen buckets.)

In parallel, the explosion of connected devices and mobility means data management is part of everyone’s life now.  The expectation now is to have access to any information you need.  Why is this not true at work?  It encourages the creation of shadow data sources.

The clash of these two developments raises the underlying question – should data be assumed to be restricted or open?  Are data guardians protecting us from imaginary dragons?  The justification for restricting data is it is not relevant to someone’s job.  How do you know?  Has anyone tried?  Some of the biggest breakthroughs come when data is connected across organizational boundaries.  What opportunities for innovation are being lost due to legacy thinking? 

The following changes are suggested:

  1. Outside of security and compliance concerns, all data should be assumed to be accessible by anyone in the organization.
  2. The onus is to provide a business case for why someone should not have access to certain data. Not the other way around.
  3. Data is a shared resource, not a scarce one. Do not manage data like you manage time or money.  It can be reused.

Interested in learning more about DataOps?  We recommend the DataOps.NEXT virtual conference by our premier partner Hitachi-Vantara.  There are 4 tracks:

  • Optimize the Data Fabric
  • Build and Manage Data Pipelines
  • Improve Data Governance and Agility
  • Expand Analytics and Machine Learning

There is no cost to join live or to watch replays for 90 days.

Date: Thu 14 May, 2020

Time: 9.00am EST / 1.00pm UTC

Where: Online

Register Now


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