Welp MagazineData is piling up everywhere, around 2.5 quintillion bytes of data are produced by each human every day and it is still increasing in 2021. Most of the online data generated are stored in centralized production systems such as databases, data warehouses, and dedicated servers. They are closely maintained, monitored, and sheltered from external requests. Analytics teams around the world receive these dynamically updated insights in a flat-file however. What if you need these flat .csv, and .txt files built into a dynamic database? This is a process called data onboarding.
What is Offline Data?
If we assume that “offline” means that a device is disconnected from an internet network, “offline” data simply means digital records that are not connected to an online environment. Typically this data is stored in applications like an Excel spreadsheet, desktop program, or local database server. Examples are contact info, third-party data from vendors, receipts, lab results, healthcare records, and so on. Offline data can easily be transferred via team collaboration tools, and email, but it could make a mess in your local download folder when you have too many of them.
What is Online Data?
Online Data is data collected from the web. They can be data generated from a marketing campaign, being user behavior data, or web traffic data it is different from offline data. Online data is usually regularly updated information streams reported from many different sources. It would require maintenance, a rigid database structure, and sometimes a data pipeline.
Benefits of data onboarding
By onboarding your data to the cloud, you may develop more value: filtering through millions of records, combining multiple data sources altogether, and producing dynamic dashboards can all be made possible in a cloud environment.
How to onboard your offline data?
1. Upload data from offline sources
Take .CSV file, for example, it can store all the disseminated data from servers in a flat file, which you can easily manage or transfer.
Uploading CSV files to an online system, however, can be a little tricky. One of the main drawbacks of offline data is that it can be messy, unstructured, and inaccessible due to missing records, mismatched schema, irregular entries, and sometimes its sheer size. By bringing data to the cloud, you can make sure that the data can be accessed and processed in one system at a much faster rate.
Try using a tool such as Acho Studio, you can easily parse your CSV file into a database management system. This way, it doesn’t matter how your CSV file looks like, you can take it to the cloud for more actions.
2. Anonymize your data
Some data records may contain sensitive information such as personal contact or private details. Post-processing your data assets may be required in compliance with data protection protocols such as GDPR and SOC2. Data entries such as personally identifiable information for example should be hidden or masked in your dataset before sharing or publishing it.
3. Aggregating your data
Once data has been anonymized and cleansed, you can start combining different tables into one good table for production needs. In this step, your main goal is to connect tables logically based on a key column that may contain IDs, emails or names. By doing so, your table should contain all necessary information for distribution.
On Acho Studio, you can use either the Join action or Merge action to combine multiple tables vertically or horizontally. By selecting the column as an identifier key, you can effectively link many tables together.
4. Distribute your data
Once your data is ready, you can share it with someone, build an application, or use it to power another tool such as an Email Relay service or Business Intelligence software. This step is done usually via a connector or API. Before sharing your data with someone, remember to assign permission to each member. Some may only be allowed to take a look, some others may not need to see certain columns. It is at your discretion to distribute data responsively and sufficiently.
Data assets can be accumulated and compounded in value over time. Some of the most powerful companies make data-driven decisions at blazingly fast speed. If you want to make your data assets more visible and liquid for decision making, check out Acho Studio for more.
