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2 min read

Data Power - Go Cloud. Choose Automation!

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Are you ready to grow your BI and Analytics, but not sure exactly how to do it?

Commonly, when looking to scale your analytics environment, this means a growing backlog, handling hesitations about the next step and receiving worrying error messages about having too little space, too few resource or too much data.

Since the latter, having too much data, isn’t really an option – as there is no option to tell the organisation to stop creating data or to start using less data as it is critical in order to gain business insights. Let’s look at the two other challenges instead.

Lack of space

I have come to believe that there is no such thing as collecting data too heavily, only understanding too slowly. With this, I will stick to the idea that we need to find room for all our data.

Yes, in the early days I too have been part of data warehouse projects, where we choose which data to keep and which to leave behind or discard all together. I too have cried many tears over the data we lost, because it obviously – at least at a later point on time – did carry meaningful value had it been available!

There are many options for saving data, like with cheap storage in-house or better yet, by putting things in cloud for others to take care of the infrastructure. These options hand us opportunities to leave behind that old-fashioned, outdated world view of discarding data due to lack of storage or ‘no immediate value seen’ (or understood or fully-realized yet).

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Lack of time and the growing backlog

This is a true bottleneck – it is hard to find those highly skilled IT specialist that talk SQL fluently and answer even the simplest email question with a Python or R statement. They are hard to come by, and it is even harder to convince them to spend their valuable time editing that 10-year-old script for loading data from an old legacy system for the tenth time this year, just to add a few more fields or change a data format somewhere.

Gain space and time

Several years ago, I would have mentioned the importance of business buy-in on data warehouse projects. Preparing them to endure yearlong projects and forcing them to describe their needs for data years in advance – only to find, that the world has moved on, when the data was finally available, making their calls outdated.

Business people of today have realized the importance of data and analytics. IT knows the importance of deciding on an architecture that enables the users to validate data across the entire organisation.

These days, our approach to data projects are more flexible. Based on our experiences, we are now able to choose a future-ready architecture. We can bring the time-to-data ratio down from several years to time measured in weeks or sometimes days. All at the same time, avoiding a lock-down on how the business will be able to use the data, as we can choose to model them to be generic and open minded.

Building an analytics environment of today could involve:

All business relevant data – better safe than sorry. If the data carries meaning, then make it available for analysis. This also means keeping your existing data warehouse as a data source.

Go cloud – The cloud doesn’t run out of storage space. Back up is taken care of and given access to the internet, your data is always available no matter where in the world you feel the need to connect to your data.

Automation – Be smart about how you use the time of your specialist resources. Invest in a platform, leverage the power of automated processes taking care of tedious, repetitive tasks. Benefit from the power of automation making your data available by loading, transforming, keeping documentation up to date, preparing and maintaining security policies - to mention a few benefits.

Does this sound simple? It can be extremely powerful.

With our innovative Discovery Hub® platform, we enhance the Data Estate through Data Platform Modernization. This enables any organization to benefit from the Intelligent Cloud and support their Digital Transformation journey from a patchwork of tools and long development cycles to an automated data platform that enables instant access to data.

Ready to make the journey to the cloud?

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