Data is everywhere—and it’s constantly multiplying. That’s why planning for big data is more important now than ever.
But most IT departments are too busy keeping the lights on, making sure systems are secure, and fielding day-to-day requests. There isn’t time to think about the future of the data itself.
Why You Need to Be Proactive (Not Reactive) with Your Data
Data volumes are going to keep growing. Forbes knows it. You know it. And we know it. That’s why you need to get a handle on your data now—before it grows out of control.
How you’ve been handling your data for decades isn’t a sustainable approach for the future. And you can’t just react to requests for data—and hope it’s enough.
The best way to handle your data is proactively.
How to Approach Data Proactively
Approaching data proactively means thinking strategically about the future of your data.
Ask yourself…
Which systems does data live in today? Where will it live tomorrow? How much data growth do you anticipate each year?
Knowing the answers to these questions will help you start thinking strategically about your data. And then you can take the appropriate measures to handle your data.
1. Put a Stop to Manual Data Wrangling
No one has time to manually query data on one-off requests anymore. And that includes your IT team.
Writing SQL queries takes your programmers’ time away from important tasks, like optimizing application performance.
And running a query in Query/400 seems faster—but you can only run one query at a time. And each time you need a different set of information, that requires a whole new query.
That just doesn’t hold up when Jen the CEO asks for data on all sales over the past quarter. And Kelly in sales asks for data on her region’s sales for the last quarter. And John in finance asks for revenue earned on those sales over the course of the quarter.
If you’re manually wrangling data, you’ll be retrieving slightly different versions of the same data three times.
It’s time to use automation and machine learning to prevent that manual data wrangling nightmare. Machine learning is key to reducing time to insight, according to Forrester research. So by automating the query process, you can query the data on the quarter once and use it to meet each request.
As your data grows, accelerating time to insight is crucial. As data becomes tons and tons of data, you need a faster way to get that data and get it to the right people.
2. Get Information from the Right Sources
You have data everywhere. But is it the right data? How can you tell?
Information is everywhere—not just in one database—and it always has been everywhere.
It’s in core business applications on IBM i. It’s in databases like Microsoft SQL Server and Oracle. And it’s in business systems and applications.
This means Kelly in sales needs data on sales that’s stored in a customer relationship management (CRM) application on IBM i. John in finance needs data stored on a Great Plains accounting system. And Jen the CEO needs a holistic view of data across every application, system, and database—including IBM i, Microsoft SQL Server, and Oracle.
So, you need a way to bring data from all different sources together into one source of truth. And you need a way to cut through the clutter of endless data to get the right data to the right person at the right time.
Using a modern query and reporting tool makes it easy to pull together data from disparate sources into one clear version of the truth.
3. Transform Data into Information
Just getting the data isn’t enough anymore. Your organization needs a way to transform data into information that anyone at your organization can consume.
Kelly in sales wants charts and graphs. John in finance wants it in a spreadsheet. And Jen the CEO wants a polished report.
For that, you need the right business intelligence and analytics tools.
Business intelligence dashboards go a long way toward transforming data into information. Graphs and charts make it easy for anyone to understand what the data means. With that kind of visualization, Kelly in sales can easily pinpoint her opportunities for the rest of the year.
Microsoft Excel is a business standard—especially in finance. By exporting trustworthy data into a Microsoft Excel spreadsheet, you can shorten the time-to-insight for people like John in finance.
Bringing data from multiple sources together into one report is challenging if you do it manually. But it’s easy if you have a smart tool by your side. Then you can give Jen the CEO the insight she needs to move the business forward and meet market demands.
How to Do Business Intelligence—Without Straining IT
You know you need BI. But what solution will work best for you and your data? Talk to one of our experts to find out.
