Every year it seems like more data is becoming unlocked and available for use by devices, applications, and platforms. That means that IT managers must make decisions on what data to collect, how to collect it and how to turn it into useful information for their end users. For many organizations, the default move is to just collect it, store it, and have it available when and if needed.
More data means more challenges however.
Information Week has a list of four of the most common ones which we've summarized below:
- Data silos
- While we are seeing more open APIs these days there are still plenty of data sources that remain difficult to access. These data silos can hold valuable information that is required by other applications to optimize their use and value to users. One way to potentially solve this is to host relevant data in the cloud. There it can be captured and stored for access by AI and other machine learning technologies to enable faster analysis and decision making.
- Complexity of data
- Large amounts of data involve massive data schemas that contain an abundance of tables, often with cryptic names, which can make it difficult to write SQL queries to retrieve it. This is where tools like generative AI can help by translating from natural language descriptions.
- Data overload
- Most organizations have adopted a practice of erring on the side of collecting and storing as much data as possible, with the mindset that it may be needed at some point. This has led to huge amounts of raw, unstructured data which, in time, can become costly to store. This is why having a data strategy is so important. Clear goals should be the drivers behind data collection. It is the best way to avoid data overload and ensure that the data collected is actually being used.
- Poor quality of data
- The quality of the data collected is often an issue. This can include everything from missing data to inconsistent and inaccurate data. What can make the quality of data even harder to control is that it may be coming from a variety of people, systems, and processes. When you have quality issues with your data it creates a lot of other issues. IT leadership must make ensuring data quality a goal, conducting regular data quality assessments and establishing protocols for the handling of the data.
At TTI we know all about the challenges that surround data. We've been working with IT managers for years, collecting billing and call data and transforming it into meaningful information that helps them save money. Optimizing data is at the core of our WinBill® and WinCall® systems, both of which provide deep insights into areas such as billing invoices, networks and equipment, contracts, and even calling patterns.
If you are an IT manager who is overwhelmed by the amount of data you need to access on a daily basis know that you are not alone. We speak to IT managers every day and we know that it's a challenging world out there.
Contact us. We can take the burden of telecom expense management off your back so that you can get back to work managing everything else.