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I keep hearing this impression that the data warehouse is obsolete. I’ve heard it at many trade exhibitions, and I’ve also read it on many blogs. I’m going to expose this, or at least get people thinking a different way that the data warehouse is not obsolete. Because here’s the point: we haven’t heard this earlier?
In 1996 Enterprise Information Integration space was generating start-ups that were encouraging to virtualize different data sources, so that you didn’t necessitate a data warehouse.
Those of us who actually have perception and know data really deeply, know that you are not able to solve the really complex data problems in easy way. It just doesn’t work in this way. The other survey that show that data warehousing is not obsolete, because 70% respondents were increasing spending for data warehouse.
So, what is actually going on?
Well, the traditional data warehouse was processing, preparing, integrating, cleaning data from different sources, but now business world got more complex.
Data warehouse architecture
Now we cloud, we have mobile, we’ve got social media data, and we have machine data, sensor data. All these are different sources. So the main issue is not the size of data but the heterogeneous data is becoming issue and business intelligence Solutions in Korea keep on struggling to find out better big data analytic tools. The heterogeneity is increasing the complexity and we are still fighting to solve this issue that how can data coming from different source analyse so that it can help to answer related to decision making and many others.
Evolving the data warehouse
In fact, we can actually employ the new technologies in ways that allow us to work a lot faster and integrate the business intelligence tools. What we need to do is just to introduce some new technologies into your organization. Bilytica is providing Big Data Snalytical Tools in Korea and data warehouse solutions to serve you to help in managing data. Don’t be late and try Bilytica Business Data Warehousing Services in Korea to bring innovation to old data warehouse concepts.