Data silos, why they are a problem and how to fix them (2023)

A data silo is a collection of data held by one group that cannot be easily or fully accessed by other groups in the same organization.. Finance, administration, human resources, marketing teams, and other departments need different information to do their jobs. These different departments often store their data in separate places called data or information silos, after the structures that farmers use to store different grains. With the increasing volume and variety of databases, data silos are also growing.

Data silos may seem harmless, but isolated data makes it difficult to share information and collaborate across departments. Data quality often suffers due to inconsistencies in data that can overlap across silos. When data is isolated, it becomes difficult for even executives to get a holistic view of corporate data.

In summary, isolated data are nothealthy data. Data is healthy when it is accessible and easy to understand across the organization. If the data isn't easy to find, timely to use, or unreliable, it doesn't add value to analysis and decision making. A company that digitizes without breaking down data silos will not be able to take full advantage of digital transformation. To become truly data-driven, organizations must provide decision makers with a 360-degree view of the data relevant to their analysis.

Enterprise-wide data analysis supports informed decision-making and a more holistic view of hidden opportunities - or threats! Furthermore, siled data is a risk in itself. data stored in silosdata officeuncontrollable across the organization, making regulatory compliance difficult and opening the door to the misuse of sensitive data.

To better understand whether data silos are limiting your potential for holistic data analysis, you need to learn more about where data silos come from, how they prevent you from getting the full benefit of data, and what you can do about it.data integrationBreak down data silos.

Why are there data silos?

Data silos naturally arise over time and reflect organizational structures. As each department collects and stores its own data for its own purposes, it creates its own data silo. Most organizations can trace the problem back to these siled data sources:

Isolated organizational structure

Beforebig dataand the cloud revolutionized business, it was not considered bad for different departments to create and createself manageData. Each department has its own policies, procedures and goals. Teams have developed their own methods of working and analyzing data that meet their needs. Silos are still built around business departments because that's how data is collected and stored.

corporate culture

Related to the above, departments in many organizations are used to working in their own worlds. Each has its own jargon, processes and challenges. By working in different areas with their own processes and goals, each department naturally sees itself as a separate business unit, distinct from other teams. This culture of separation carries over to the data. Even if the sales team and marketing team work with customer data, company culture may encourage them to keep their data separate, even without questioning it. Since sharing data across the enterprise is a relatively new goal, departments were not motivated to unify their data.

Technology

The very technical tools and data management systems that many companies use have pushed them into data silos. Different departments tend to support their operations with different technology solutions and tools, e.g. B. spreadsheets, accounting software or a CRM like Salesforce. Most legacy systems were not designed to easily share information. Each solution stores and manages data in different ways — it often belongs to the vendor that built the solution, making it difficult to share records with stakeholders in other departments.

4 Ways Data Silos Are Quietly Ruining Your Business

Each department exists to support a common goal. Although the departments work separately, they are also dependent on each other. At least some of the internal data that, for example, the finance department creates and maintains is relevant for analysis by management and other departments.

Competition, the need to reduce costs and the desire to seize opportunities are driving organizations to do more with their data. access tocompany-wide informationit is necessary to maximize operational efficiency and discover new opportunities.

But at some point, data silos will get in the way of success. Here are four common reasons why data silos hurt business:

1. Data silos limit data visualization

Silos prevent relevant data from being shared. Each department's analysis is limited by its own perspective. Without an enterprise-wide view of data, there is no hope of uncovering enterprise-wide inefficiencies. For example, how can you find hidden opportunities for operating expense savings when operating and cost data is not consolidated?

2. Data silos threaten data integrity

When data is isolated, often the same information is stored in different databases, leading toInconsistencies between department data. As data ages, it can become less accurate and therefore less useful. For example, if the same patient's medical data is stored on different systems, that data may become out of sync over time.

3. Data silos waste resources

When the same information is stored in different locations and when users download data to their personal or group storage, resources suffer. Optimizing data at one source frees up valuable storage space and frees IT from buying and maintaining storage it may not need. For example, if many employees download data to analyze in a spreadsheet, each download is aredundant copyfrom existing data.

4. Data silos make collaboration difficult

Culture creates silos and silos reinforce culture. Data-driven companies use collaboration as a powerful tool to find and leverage new insights. To promote collaboration, departments need to be able to share their data. When data is difficult or impossible to share, the ability to collaborate suffers.

How to break data silos in 4 steps

The solutions to silos are both technological and organizational in nature. centralizationdata for analysisit got much faster and easierClouds. Cloud-based tools simplify the process of gathering data into a common pool and format for efficient analysis. What used to take weeks, months or years can now be done in days or hours.

1. Change Management

If organizational culture can create data silos, this is also the key to breaking data silos. Communicate the benefits of sharing and data integrity so employees understand the change. Also communicate issues with silos, including data quality issues and the need to stay competitive. Culture change is a big undertaking, so management needs to show commitment.

2. Development of a method for data centralization

When it comes to data management systems, the best way to break down silos is to consolidate all corporate data into a cloud-based data warehouse or data lake — a central repository of data optimized for efficient analytics. Data from disparate sources is homogenized and consolidated, and access can be easily granted to individuals or groups to balance business needs with privacy and security.

3. Integrate data

Integrating data efficiently and accurately is a sure way to avoid future data silos. Organizations integrate data using one of several methods:

scripting
Companies can hire IT to write scriptsSQL, Python, or other scripting languages ​​to move data from isolated data sources into the warehouse. The downside of scripting is that it can be complex. As data sources grow, so does complexity. Changes to data sources require a script update. Maintaining a hand-coded integration becomes a cost and time burden for IT professionals.

Lokale ETL-Tools
ETL(extract, transform and load) andELTThe tools automate the process of moving data from multiple sources into the data warehouse. These tools extract data from sources, transform data into a common analysis format, and load the result into a data warehouse located in the organization's data center.

cloud based ETL
Cloud and data go hand in hand, and sophisticated cloud providers make the ETL process easier and faster.cloud based ETLuses the cloud provider's infrastructure – including a data warehouse andETL Toolsdesigned to work efficiently in your environment. ETL breaks down silos by providing the technological means to collect data from multiple sources in one central location for analysis. ETL helps address data integrity issues so everyone is always working with up-to-date data.

4. Set up regulated self-service access

When data is centralized and integrated, you also create the ability to centralize data access and control with oneData-Governance-Framework.Robust data access policies facilitate self-service analytics, so business users with permissions can easily access the data they need, without the headaches or delays that come with having IT staff act as gatekeepers.

The cloud and the future of data storage

The cloud has evolved as a natural way to centralize data from disparate sources for easy access in the office, at home, on the go or in branch offices.

Cloud data solutions help remove technology barriers to collaboration and provide a turnkey solution for connecting siled data. Using an established ETL process to remove irrelevant data and eliminate duplicates, organizations can quickly add new and updated data to a cloud data warehouse. This allows different departments to collaborate on up-to-date, clean and timely data on a single, accessible platform that can scale as needed.

Cloud technology and cloud data warehouses connect disparate business areas into a cohesive ecosystem. Data analysts gain better insight into how their work affects the entire organization and how other people's work affects each other. Access to enterprise-wide data gives analysts a 360-degree view of the organization.

Dismantling data silos

Data silos hurt productivity, hamper insight and hamper collaboration. But silos are no longer a barrier when data is centralized and optimized for analytics. Cloud technology has been optimized to make centralization feasible.

Thousands of companies around the world choose to centralize their data in the cloud with Talend Data Fabric because Talend simplifies ETL data integration, data governance, security and regulatory compliance, while providing all departments with access to silo breaking data. For example, Covanta – a sustainable energy company – has made it a priority to break down data silos so they can better collect, manage, transform and share data. Once departments across the organization communicated with a common source of truth in real time, they could easily find and eliminate inefficiencies.monasteryreduced the cost of maintenance activities by 10% per year.

Talend Data Fabricenables users across the organization to collaborate with a comprehensive set of applications - a solution to simplify the process of breaking down silos forever. You canExperience a Talend Data Fabricto see for yourself how Talend can work with you to eliminate silos, improve operations and increase profits across a variety of use cases. We help you break down data silos and ensure that decision makers in your organization always have a comprehensive understanding of corporate data.