Having The Power Of Data Visibility Makes It Easier And Faster To Make Decisions To Support Your Digital Transformation Strategy And Goals.
We live in a world full of data. Even in organizations with conventional IT departments, the amount of data and information they collect from their systems, processes, customers, and products has increased dramatically in recent years.
When we go back to the past, we see that IT data was kept in silos due to the fragmentation and isolation of the systems as well as the data generation and collection mechanisms. That is why the communication and internal dependence on the data in such separate environments have been at their worst.
With the growth of public clouds and the related services they provide, the ability to break down the walls of these silos and the pool of data mixed within them is greater than ever. Companies and organizations welcome these opportunities.
However, more significant volumes of data generated by new systems and services will be available along with new business and operational models.
Maybe a few years ago, IT data was not rich and robust enough to fully support the needs of various stakeholders within a group, such as CFOs and CIOs, but now the situation has changed.
We are in a new era where partners and stakeholders have access to all the data they need to make better business decisions and can do so much faster than ever before.
We can now extract meaningful and relevant data previously impossible or complicated to obtain and have a complete view of all resources spread across the IT department.
Select, organize and calibrate
The challenge we face right now is to select, organize, and calibrate this vast amount of information so that IT leaders can act faster and make better decisions. The possibility of gathering data from all different parts of the IT field means that now is the time to pursue meaningful and new questions. What amount of information can be more than we need? The answer to this question is debatable. Is all this information relevant? Maybe no.
Technology value optimization tool
So how can we avoid incorrect analysis resulting from having a massive amount of data? The good news is that the means of collecting and storing this data have constantly been changing and evolving.
The Technology Value Optimization (TVO) tool helps companies and organizations to predict and map the state of their entire IT and make data-driven decisions that align with their organizational goals.
Choose tools and methods available in the market (from both cloud service providers and third-party vendors) that help you extract unique and relevant points from all this data, then add more information to those data points.
Add up to make good decisions faster and more agile with good data. Normalized data from various sources can help you make data-driven decisions. As a result, you will be able to increase the efficiency of your business.
In the discussion of data analysis or data analytics, while the quantity of data comes into play as the law of large numbers and makes these findings statistically significant, the data quality is more critical.
As you can see in the image below, in the past, the main challenge for IT professionals in making forward-looking decisions was the lack of data. They did not say there was not enough data, but instead that their concern was not enough data to be confident.
Good data supports better and faster decisions.
There is a famous sentence that is an example of this issue. “What you can’t assess, you can’t manage.” With the tools and services readily available in modern IT systems for data collection, we can safely say that we have found many ways to conduct appropriate assessments. The current situation has changed from the data set question to the data’s validity and relevance.
By referring to history, we see that even with good data, it is possible to make a wrong decision. Of course, the opposite is also true. Making good decisions with insufficient data is extremely difficult. For example, if we fail to normalize the available data set or remove redundancies, there may be more data points to support the decision when there aren’t. As a result: forward-looking strategic choices may be based on results that are not always on the same line.
As more workloads are evaluated to be deployed in public clouds, the need for clean and accurate data becomes even more critical. An organization needs to pay more attention to its IT assets than it can handle. The interaction between all these services and existing tools should be completely transparent, and it should be clear which of them is at the end of support time (EOS) or which is nearing the end of life (EOL).
Having a list of “what’s” is essential in IT, but it’s tough to make good decisions from the piles of collected data without normalizing, cleaning, and strengthening that data.