The world of enterprise business lives and breathes data. From every decision that it makes to the comprehensive analysis of trends, data is seemingly present at all stages of business operations. Yet, although it is incredibly pervasive, many businesses are still not adapting to modern best practices for managing data.
Many businesses still suffer from data isolation, which is where data is siloed within different departments, applications, or systems. If data is isolated in segmented areas, then it cannot readily flow, resulting in limited accessibility, integration, and visibility.
In order to create a data-driven culture that uses high-quality data and analytics to make smart decisions, organizations must attempt to dismantle any occurrences of data isolation.
In this article, we’ll dive into the world of data isolation, exploring the core characteristics and impacts of data siloing and offering a number of solutions to improve the natural flow of data across a business.
Let’s dive right in.
What are the Characteristics of Data Isolation?
If you’re unsure if your enterprise is currently suffering from data isolation, it’s important to take some time to assess your current data management, storage, and sharing practices. Without a free flow of data across an organization, it can rapidly succumb to poor data quality, ineffective practices, and redundant analysis.
In order to spot data isolation, your business should look for the following impacts on your data management and analysis.
Limited Access to Data
One of the most obvious issues that data isolation causes is limited access to data. If you’re looking for this inside your business, a great way of doing so is by approaching data storage from two different departments. For example, if you look at which data resources your marketing department has against what your HR department has, you may quickly notice that data is not being shared effectively.
Limited access to data means that when people make data-driven decisions, they are using a reduced amount of information. Not only does this lead to bias and inconsistencies, but it can also mean that whole departments are taking action on ineffective data. Finally, a limited amount of visibility between departments will radically decrease collaboration, dismantling cross-department communication and coherence.
Data Inconsistency
Data inconsistency and redundancy refer to any data that is duplicated with many versions being spread out across a network. If there are several data silos in your organization, you might be storing replica data several times over. Beyond just creating an operational inefficiency, this can lead to your business paying more for cloud storage due to all of the replicas increasing your total required storage space.
Alongside storage inefficiencies, data inconsistency can introduce even more issues in a business when it comes to transaction data. If your business is using siloed data for transactions, then two departments could have access to extremely different numbers for the same piece of data.
As data inconsistency increases, the likelihood that your business will make mistakes due to poor visibility also increases.
Reduced Integration
Data isolation creates major problems when it comes to the active integration of new data. Typically, a data-driven business wants to put from all of the data it has available, creating unique insights from a range of sources. However, when data is isolated into several silos, data integration becomes significantly more challenging, reducing its overall productivity.
Without clear access to all of an organization’s data, data analytics, reporting, and BI efforts become ineffective. Across all of a company’s workflows and processes, siloed data increases the time it takes to create insight while also reducing the worth of analysis.
In the short term, this can create cross-department frustrations. In the long term, data isolation can reduce the overall success of a business by impacting its ability to streamline business operations and draw insight from data.
How Can a Business Overcome Data Isolation?
Once you’ve identified data isolation within your organization, you should endeavour to remedy it as soon as possible. While this won’t be an overnight solution, there are many tactics that you can employ to increase data visibility, observability, and cohesion.
Here are some typical strategies that businesses can use to overcome data isolation:
- Data Consolidation: One central cause of data isolation is poor data integration and consolidation strategies. If a business is incorporating data from different sources into silos instead of a centralized repository, it will decrease visibility and access to data. When reviewing your data architecture, make sure to explore the data consolidation capabilities of your analytics platforms. For example, when comparing Snowflake vs Databricks, we can see both offer distinct services in terms of integrating data from different sources. Be sure to match your data architecture with what your business is looking for.
- Data Governance: Standardizing your organization’s approach to data governance and regulation is one of the most effective ways of dismantling data isolation. By providing clear guidelines on how data should be managed, stored, and shared, you are able to rapidly ensure that your employees are correctly handling data. Beyond just increasing accessibility, data governance procedures will reduce inconsistencies in your data and promote the healthy management of new data.
- Modern Data Structures: Beyond just using a data warehouse, expand your data storage capabilities by investing in alternative data structures. Incorporating structures like data lakes can help to increase your organization’s ability to store unstructured, structured, and semi-structured data in centralized repositories.
Although the above strategies are not exhaustive, they will allow an organization to get started with more data-collaborative approaches. Each of these strategies pushes a business to become a more data-driven organization, helping to remove data isolation and promote effective data management strategies.
Fostering both technological and cultural change when it comes to the management and treatment of data will help ensure your organization never has to suffer from data isolation again.
Final Thoughts
As we progress further into this age of data-driven analysis and operation, overcoming data isolation is more important than ever before. Being able to integrate data across many sources without leading to silos will provide flexible, accurate, and comprehensive backing for effective data analysis and insight generation.
Data isolation is easy to spot but hard to begin to dismantle. However, by following the methods we outline in this article, your business will be able to push back against isolation and begin to break down the silos that you currently rely on. Once you have a homogenous, accessible data storage system, your entire business will be able to benefit.