Data centralisation is no myth for smaller organisations
While smaller companies may have fewer resources compared to larger enterprises, they can still benefit from centralizing their data. Data centralization is core to digital transformation because it enables organizations to consolidate and harness their data in a unified and accessible manner.
Here’s how data centralization can be done in a smaller company:
Assess Data Sources
Identify the various sources of data within your company, including databases, spreadsheets, documents, and software applications. Determine what types of data are critical for your operations and decision-making processes.
It is also important to understand where the data in those sources are coming from, who accesses and uses that data and what kind of risks the data source has. This will be important when designing your data integration later on.
Define Data Governance Policies
Establish clear data governance policies and guidelines that outline how data should be collected, stored, organized, and accessed. Define data ownership, data quality standards, and data security protocols.
Choose a Centralized Data Storage Solution
Select a centralized data storage solution that aligns with your company’s needs and resources. This could be a cloud-based storage system, a database management system, or a data warehouse. Consider factors such as scalability, security, accessibility, and affordability.
You might want to go with a free or open-source database such as MySQL or PostgreSQL but know that these still come with the question of where the database should be hosted. Hosting and maintenance costs will still apply. You can also consider a cloud option that has hosting and maintenance costs taken care of as part of your subscription fee. Many specialised data integration platforms can host a database for you.
Data Integration
Integrate data from various sources into the centralized storage solution. This may involve data extraction, transformation, and loading (ETL) processes. Leverage tools and technologies that enable seamless data integration and ensure data consistency.
For example, a platform that allows you to import data from various sources via connectors quickly. This way your team does not need to write code for each source. You can simply drag a connector into your process and configure it. A platform such as Linx also allows you to perform data mappings, apply data validations and transformations and build flexible and bespoke data-loading processes with orchestration.
Data Cleaning and Standardization
Cleanse and standardize the data to ensure accuracy, consistency, and uniformity. This includes removing duplicate records, resolving inconsistencies, and normalizing data formats. Implement data quality checks and validation processes to maintain data integrity.
This can be facilitated by using a specialised platform. You can build these validations and transformations into your data-loading process, and you can even create and send data quality reports to responsible parties, highlighting issues that need to be corrected.
Access Controls and Security
Implement access controls to ensure that only authorized individuals can access and modify the centralized data. Establish appropriate user roles and permissions to protect sensitive data. Implement security measures, such as encryption and regular backups, to safeguard the centralized data.
Enable Data Accessibility and Collaboration
Provide employees with appropriate access to the centralized data based on their roles and responsibilities. Implement tools and technologies that facilitate data discovery, searchability, and collaboration. This can include data visualization tools, reporting tools, and shared documentation platforms.
A specifically useful way of making data accessible and available through your organisation will be via an internal API. With a platform you can usually build and host APIs with ease, making the data accessible in real-time. For example, you can create a very simple and straightforward data read REST API using a wizard to provide specific data to other applications and users in your business with Linx.
Another idea for data accessibility is to provide reports or data extracts via Excel. This process can also be automated in its entirety, in such a way that the files are delivered via FTP or Email.
Establish Data Maintenance Processes
Implement processes to update and maintain the centralized data regularly. This involves ongoing data governance, data quality monitoring, and data hygiene practices. Assign responsibilities for data management and establish workflows for data updates and maintenance.
Here it is a good idea to implement data maintenance reports, highlighting how many issues were picked up during data quality checks, how many issues have been resolved, highlighting issues that need to be resolved and more. These reports can be emailed to responsible parties.
Data Analysis and Insights
Leverage centralized data to gain valuable insights through data analysis and reporting. Utilize analytics tools and techniques to extract meaningful information from the data. This can help inform decision-making, identify trends, and drive business growth.
A platform can assist with the process
Many of these processes can be built by a single platform. This will ensure that your processes are standardized and quickly created. There are a few available on the market, I prefer to use Linx because it is what I am comfortable with. You can also look at Talend, Snowflake, or even SSIS.
Linx allows you to build bespoke and flexible data integration solutions at speed as the entire process can be built, from data loading to delivery, in a single platform. Because Linx works as low-code coding — not workflow — there is an inherent amount of freedom and flexibility to cover the bespoke nature of BI applications. Being a platform, your solution is hosted on a Linx server, without the need to figure out infrastructure or deployment processes.
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