According to numerous studies and charts (for example Forbes 2000 and 2017) up to 80% of the biggest world organisations are aware of the value of the data and recon data among the main assets. During last years the investments into data processing and analysis took quite a significant part of the organisations‘ budget. Data engineering has been the fastest growing technological role. In spite of that only a few organisations have achieved a significant (positive) financial impact.
Historically, mainly financial organisations invested into data analytics , as they have been working with data by its very nature. Soon after that as well companies from different sectors started to discover the power of data and derived information. It is clear how powerful differentiator can be the proper utilization of data. Good examples are Stitch Fix, John Deere, Netflix or Nubank. We can even say that the more commoditized the company’s sector is, the more important is the need for advanced use of data, data analysis and search for differentiators that could shift the company forward. In the Czech environment Rohlik.cz is a nice example of a company that uses data analytics to provide optimized service for its customers and therefore highly differs from its competition. Furthermore, the data assets started to be traded between companies and the data itself monetized.
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The development of platforms, technologies and tools in the data area can further extend the possibilities of what for the data can be used. It does not matter anymore what is the data source (the data source doesn’t necessarily have to be the company’s internal systems), the structure (voice, video, pictures) or its volume. At the same time, the possibilities of how to use the data, are growing. It is starting with classical reports and dashboards, continuing through the Data Science and getting close to AI. The data became inseparable part of company processes. The technologies aim to be easy to use not only for professional IT specialists, but also for common users. The data are gradually turning into a service rather than a product created „on demand“ by dedicated data department.
Cloud solutions simplified the access to necessary technologies even for companies that haven’t been forced (or hadn’t have the resources) to invest into their own in-house solutions. To establish a complete environment that is suitable for working with data and retrieving the valuable information is today a questions of weeks rather than months to implement. Cloud technology also requires considerably less in-house technical knowledge.
The factors listed above shifted the means of working with data considerably forward (but, mainly from the technical point of view).
The democratization of data and tools hand in hand with cheaper solutions and services leads to new challenges. There are more and more users that need to work with data on a daily basis. The users require more data and much more flexible access. „Own“ place where it is possible to analyse and process the data along with suitable tools become a must.
However, new users often do not have enough experience with data analytics.
To achieve positive financial impact the companies need to invest not only into data democratizing technology, but as well into (and I would say these days especially) into company culture and data user literacy.
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Everything mentioned above are challenges for the traditional Business Intelligence (BI), which has been established for decades as a standard in the world of data. Monolithical BI solutions had been previously built usually for the needs of regulatory and management reporting. Therefore these solutions have been built with a robust governance and processes. The main focus was on internal structured data and its central based integration. The data perspective was rather retrospective – describing the past. Everything was typically based on theoretical „one version of the truth“ and therefore based on definition, central model and implementation that suited no-one in the end.
The traditional BI world provides data more like a product, reflecting the possibilities and demands it had been built within. However it is usually not very accessible and flexible for business users. The former top management reporting has gradually turned into more detailed and complicated solutions. With growing number of requirements BI based on DWH became slow and inaccessible and very expensive.
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Nowadays there is more pressure on flexibility, speed, accuracy and the ability to use the data for business development.
The conflict between standard BI’s lack of flexibility and business user needs usually caused creation of „shadow solutions“. People create and flexibly adjust their own/local solutions as they need. This is the cause for another extreme – creation of a world of isolated personalised solutions within company departments. This “data anarchy” leads to a completely opposite effect that for what BI was created. For companies such state is very contra-productive and is often causing that decisions are based on locally processed data and therefore often incorrect.
The new, data democratic world should answer this situation. Its goal is to adapt and use new possibilities to better meet the frequent business needs. The new world needs to be able to balance the governance with the need for scalability, accessibility, flexibility and self-service for everyone who wants and is able to use the data for his daily agenda.
The topic of the Data driven company has been resonating through the world of data in the past few years. To become Data driven is one of traditional strategic targets of financial companies in the past 5 years. What is a Data driven company and on what principles it is possible to build one? That is a topic for our future articles.
