Unifying Business Data: Breaking Down Data Silos

Enterprises are handling massive amounts of data than ever before. This has led to processes working in a siloed way, which has further resulted into disconnected pools of data. Breaking down data silos can be difficult. Almost 60 percent of business leaders cite organisational data silos as the biggest impediment to effective decision making. Typically, data silos occur when your organisation uses mutually exclusive IT systems. With more data volume comes more complexity to be able to effectively handle and utilize that data. 

For many enterprises, the data they hold may be their most valuable asset. In addition, there isn’t adequate planning to manage the massive amount of data that they hold.

This leads to the creation of data silos which can hamper productivity, and lead to additional operational costs. Data silos can impact decision-making which holds a business back from its true potential.

Data Silos : Intentional or Unintended?

87% of organizations have low analytics and business intelligence maturity. It means the data isn’t being utilized to its full potential. For example:- In a regulated business like a health care provider where a small group of people are only meant to be able to access and manipulate private patient data. In such cases, data silos may be entirely intentional, but for most companies this is rare.There may be some forms of data that are only meant to be accessed by certain people or teams due to sensitivity of the data i.e how the data is supposed to be used.

However, unintended data silos can occur too. These generally arise because different departments use different software solutions or processes to manage the data, creating a barrier between departments. This may cause delays, and inefficiencies.

The Impact of Data Silos

What’s the big deal? So data silos have formed within an enterprise.

Data silos can be a massive hindrance to the company’s growth and operational efficiency of a business. Because it impacts decision-making. If decision-makers at all levels cannot easily access the data needed it can lead to skewed context. This eventually snowballs into lower productivity and increased costs. As inefficient workaround solutions are adopted to tackle this. 

If a team member needs to reach out to someone else on another team in order to complete a task then this can cause a delay. When employees feel like processes are out of their control and holding them back from doing their best work, that’s a big problem. 

Identifying Data Silos

Identifying and breaking down data silos is an important goal of any digital transformation effort for enterprises. Data-driven organizations are 

• 20X more likely to acquire customers
• 6X as likely to retain customers, and 
• 19X as likely to be profitable as a result

Breaking down these silos is about more than just the data. At the macro-operational level, these data silos are preventing the most efficient operation possible, by splitting organizational data.

By targeting data silos, management is making a commitment to become more efficient and embracing change.That should trickle down throughout the organization and lead to overall better productivity or a better attitude toward change and digital transformation.

Breaking Down Data Silos with CloudIO FLOW

In a recent MarketWatch survey, almost 69% of CFOs said that keeping information siloed in departments is the most common financial mistake that enterprises make today.

The first step is to adopt a standardized data model for the entire enterprise. Simply put, if different departments are working with different models and software solutions, then data silos will begin to grow as the amount of data within departments increases in isolation. 

Next, new data policies and controls need to be adopted. Not everyone can access and work with every piece of data within the organization. But, creating these policies can help identify the silos. The ones that need to be broken down and the ones that need to be retained in order to ensure the integrity of the business. Finally, data needs to be accessible. 

CloudIO helps enterprises unify their business data seamlessly by helping them tackle these data silos. CloudIO FLOW is a modern, scalable, real time data pipeline. CloudIO FLOW can be deployed on-premise or on private cloud, which means, your data stays within your systems/network. CloudIO FLOW can be used to stream data from various inputs such as Relational Databases (like Oracle, SQL Server, PostgreSQL, MySQL etc.), or SaaS systems such as Salesforce, Workday or any system that exposes REST API or database access and Cloud Storage (such as Amazon S3, Google Drive, Azure Blob Storage and traditional sources like SFTP & File System).

Once the data is imported into the pipeline, it is streamed through various stages such as Data Masking of some sensitive parts of your data, validations, transformation, actions and mapping to the output schema and then automatically loaded into the output (data lake such as Redshift, Azure SQL, Snowflake, S3 or any Database) for analysis and reporting. Most importantly, it enables the creation of new business applications rapidly utilizing data from data lakes or enabling them for external consumption through APIs.

This could include adopting new workflow tools and implementing automation where necessary. This enables enterprises to leverage a multi-pronged approach that can help address process silos and optimize overall operations.

To learn more on how CloudIO can help you tackle your data silos and unify your business data, get in touch with us.