Beyond Backup: Building a Complete Data Strategy for Small Businesses

Backups are an excellent information security measure. Everyone knows that. But businesses having massive amounts of money on the table are prime targets of cyberattacks. Unfortunately, not many startups know any better than just backing up the company data. 

For a full-fledged business, backups are just one of the many elements that are essential for safeguarding company resources. Big businesses have an entire data governance framework at their disposal to minimize the risks of cyberattacks and information leaks.

According to CIAB, 60% of small businesses die out within 6 months of getting hit by a cyberattack. So, even small enterprises need to learn from big ones and create a straightforward, holistic data strategy. 

In this article, I’ll answer why backup isn’t enough and the cost of bad data. The following section will list the components of a database governance framework and how you can build one for yourself, leveraging AI data analysis tools.

KEY TAKEAWAYS

• Data backups aren’t enough to save you from cyberattacks.
• Getting out of business is almost certain for a startup if you get hit by a cyberattack.
• AI is really helping small businesses with records management.
• You can also build a data strategy just like big businesses have implemented at them.

Why Backup Isn’t Enough

Backing up files is great, but it’s just that it’s not enough. 

It’s not enough to protect the data; forget about its proper management.

How do we utilize the business data?

Every day, startups are gathering useful information. Customer records, sales history, website analytics, email open rates, social media engagement, etc. All this can be leveraged to improve a business. However, if there is no strategy to clean, organize, analyze, and act on it, it just sits there doing nothing.

A backup saves data. A strategy helps put it to work.

The small businesses that win are the ones finding ways to use their information to stay one step ahead of the competition. AI-powered tools for data analysis enable small enterprises to compete with larger businesses that have more resources. These tools can identify trends, analyze customer behavior, and predict future outcomes so small businesses can pivot as needed.

Pretty incredible when you think about it.

But first, let’s go over why this is so important.

The True Cost of Bad Data

Among IT security concerns, most businesses fear information loss. And, once a cyberattack strikes, leading to data loss, most of them can’t recover from that either.

Can you imagine the number of businesses that have poured time and money into backups just to suffer catastrophic data loss? It’s tragic.

According to DataNumen, 85% of organizations experienced one or more data loss incidents in 2024. And if the data loss is prolonged, affecting more than 10 days of saved information, that number jumps to…

93% of businesses go bankrupt within a year.

Thankfully, it is not all doom and gloom. Some steps can be taken to avoid both data loss and poorly managed records.

Components of a Data Strategy

A robust data governance framework can prevent all these awful, catastrophic events. 

But what about all of the data that is already sitting there unused? All of the purchasing information that was entered into Salesforce last month? What about that customer feedback collected via SurveyMonkey last week?

A data strategy involves every stage of the data lifecycle. From collection, storage, and analysis, to creating actionable workflows based on those insights.

Here’s what a database governance framework should involve:

• Data collection: What is needed and how will it be collected?
• Data storage: How will that be stored securely (including backing it up)
• Data quality: How will it stay clean, accurate and consistent?
• Data analysis: How will it turn into useful business insights?
• Data security: How will sensitive business information be protected from threats

Each of these aspects relies on the other. Without a strong foundation, a data strategy will fail.

Think about it. What good is collecting information if there is no way to analyze it? Or it gets collected but never stays clean?

On the other hand, if a strategy covers all data needs… that’s a winning formula.

INDUSTRY FACT
According to Mastercard, 43% of all cyberattacks are targeted at small businesses.

Leveraging AI Data Analysis Tools

Ahh, that thing that is making noise all around is mentioned: artificial intelligence.

Businesses have been using raw data to turn it into usable business insights. But with AI data analysis tools, it’s being done at a breakneck speed. Where once it may have taken hours or days to build a custom spreadsheet, now these tools do the heavy lifting in a matter of minutes.

Startups are already hopping on board. According to a recent survey by Thryv, small business AI adoption grew 39% in 2024 and is expected to grow another 41% in 2025.

Here’s what the right AI tools can do:

• Automatically identify patterns and trends.
• Predict future outcomes based on historical data.
• Automatically generate reports that would otherwise be built manually.
• Clean up information by finding duplicate entries, mistakes and inconsistencies.

The businesses that adopt these tools now will leave the competition behind. And those that don’t adopt them will be left wondering why all their data does nothing but sit on a dusty hard drive.

How to Build Your Data Strategy

Okay, let’s get to the main course. Just follow the given steps, and you’ll have a robust information governance framework for your startup. 

Step 1: Audit what data already exists.

Take stock of all the information the business currently has. Where is it coming from? Where is it being stored? Who is in charge of it? It’s surprising how often businesses will outgrow their database management without even realizing it.

Step 2: Identify the goals.

What is the business hoping to accomplish by leveraging its data? Increase sales? Decrease customer churn? Improve marketing ROI? Whatever the goal is, make sure it is SMART (Specific, Measurable, Attainable, Relevant, Timely).

Step 3: Choose the right tools.

This is where the AI data analysis tools come in. Don’t break the bank but don’t cheap out either. Do the research and find the best tool for your business needs and budget.

Step 4: Cultivate a data culture.

Make sure everyone on the team knows why this is important. If they don’t, it’ll be difficult to get them on board to leverage historical information into their day-to-day decision-making. Data-backed decisions should be the norm, not the exception.

Step 5: Review the strategy.

Just like with any other component of a business, the data strategy should be regularly reviewed and improved when necessary. As the business grows and changes, so will the strategy.

Wrap Up

Backing up is one of the steps in a comprehensive data governance framework.

There is so much more that goes into managing sensitive information than just making sure it can’t be lost. And thanks to modern AI data analysis tools, small businesses have more opportunities than ever to leverage their information.

To recap:

1. Audit what information exists and where it comes from.
2. Identify what the business wants to achieve with its data.
3. Choose the right tools for the business.
4. Teach the team the importance of using data.
5. Consistently review the strategy and improve it.

Small enterprises that implement a proper strategy will leave their competition in the dust. Don’t wait for a data disaster to be the wakeup call. Start building that strategy today.

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