Intro:
In our digital age, the art of capturing and storing data in the vast expanse of the cloud has become second nature. It’s a reflex born out of the fear of missing out (FOMO) on a valuable piece of information, as if each byte carries the potential to unlock a hidden treasure trove. This convenience, however, has birthed an inadvertent accomplice – the rising trend of what we call Data Hoarding Disorder.
In the pursuit of information, we've cultivated a habit of saving data without a second thought, oblivious to the accumulating costs that quietly nibble away at the efficiency and resources of our businesses. The ease of dumping data into the cloud has created a deceptive comfort, shielding us from the tangible consequences of our digital packrat tendencies.
Why behind Data Hoarding Disorder?
Data is like a storyteller in the modern era, revealing important information that can help us plan and act. It is a precious resource, but its real strength depends on how well we can sort, examine, and interpret the huge amount of data we collect. Depending on our goals and needs, we can use different types of reporting to make sense of data and derive insights from it.
Operational reporting helps us monitor and manage our daily operations by providing detailed reports, lists, and summaries of data. It tells us what is happening in our business processes and activities, and alerts us of any issues or problems that need our attention.
Tactical reporting helps us measure and improve our performance and efficiency by providing summary, performance, and exception reports of data. It tells us how well we are achieving our objectives and targets, and allows us to perform what-if analysis to explore different scenarios and outcomes.
Strategic reporting helps us plan and project our future direction and growth by providing mostly planning and projection reports of data. It tells us where we want to go and how we can get there, and enables us to forecast and anticipate trends and opportunities.
|
Reporting Type |
Characteristics |
Time Horizon |
Information Output |
Technology Recommendation |
|---|---|---|---|---|
|
Operational Reporting |
•Transaction or Event based reporting •Reports are well defined and structured •Critical with high business impact |
Real-Time |
Detailed report , Lists and summaries |
Reporting directly out of System of Record. Canned reports |
|
Tactical Reporting |
•Rolled up summary of data across platforms •Data processing is more focused with interpretation and consistency •Decision analysis / response to queries •Smaller data set (months worth of data) |
Near Real-Time |
Summary , Performance and exception reporting What-if analysis |
Snowflake or other databases such as SQL server, Cosmo DB |
|
Strategic Reporting |
•Aggregated data, external system reference data •Integration with external data sources •Mostly simulation and graphical •Larger data set (years worth of data) |
Historical |
Mostly Planning / Projection |
Snowflake, Azure Data Lake |
Some of the consideration for data storage are
Storage Costs:
Cloud storage may seem limitless, but it’s not free. Organizations pay for the space they use, and as data accumulates, so do the expenses. Unused or redundant data contributes to unnecessary costs.
Processing and Maintenance:
Data requires processing, indexing, and maintenance. The more data you accumulate, the more resources you need to manage it effectively. This includes backups, security, and compliance efforts.
Complexity and Performance:
Large datasets can slow down systems and impact performance. Querying and analyzing vast amounts of data become more challenging, affecting decision-making processes.
Risk and Security:
Storing excessive data increases the attack surface for security breaches. The more data you have, the more potential vulnerabilities exist.
Legal and Compliance:
Retaining data indefinitely can lead to legal and compliance issues. Regulations like GDPR require organizations to manage data responsibly.
Opportunity Cost:
Focusing on relevant, high-quality data allows businesses to extract meaningful insights. Hoarding data may divert attention from valuable analysis.
How to Manage
Data Governance: Establish clear policies on data retention, archiving, and deletion.
Regular Audits: Periodically review stored data and assess its relevance.
Purpose-Driven Collection: Collect data with specific goals in mind.
Cost Awareness: Educate teams about the true cost of data storage.
Remember, data is an asset, but managing it wisely is crucial for efficiency, security, and cost-effectiveness
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