How Can Data Virtualization Help You Get the Magical Soup Stone?
If you ever attended some of my keynotes, you have probably heard me talk about the magical soup stone story as I relate it to how organizations can build the right data strategy and become a data-driven organization. In this post, I will only focus on and share how a technology called “Data Virtualization” could be one of the pillars of the magical soup that helps in building data-driven organizations.
But first, let me tell you the story…
“Once upon a time, somewhere in post-war Eastern Europe, there was a wandering soldier who came to a small village, tired and weary from his long journey. The traveler did not have anything to eat and hoped that a friendly villager would be able to feed him. “There’s not a bite to eat in the whole province,” he was told. “Better keep moving on.” “Oh, I have everything I need,” he said. “In fact, I was thinking of making some stone soup to share with all of you.” He pulled an iron cauldron from his wagon, filled it with water, and built a fire under it. Then, with great ceremony, he drew an ordinary-looking stone from a velvet bag and dropped it into the water.
By now, hearing the rumor of food, most of the villagers had come to the square or watched from their windows. As the soldier sniffed the “broth” and licked his lips in anticipation, hunger began to overcome their skepticism.
“Ahh”, the soldier said to himself rather loudly, “I do like a tasty stone soup. Of course, stone soup with cabbage — that’s hard to beat.”
Soon a villager approached hesitantly, holding a cabbage he’d retrieved from its hiding place and added it to the pot. “Capital!” cried the soldier. “You know, I once had stone soup with cabbage and a bit of salt beef as well, and it was fit for a king.”
The village butcher managed to find some salt beef . . . and so it went, through potatoes, onions, carrots, mushrooms, and so on, until there was indeed a delicious meal for all. The villagers offered the soldier a great deal of money for the magic stone, but he refused to sell it and traveled on the next day.”
So, how can we learn from this story to make a magical soup with the help of data virtualization technology?
Motivate the sharing of ingredients -“data”:
At first, data virtualization could be one of the ways to help people share their ingredients or “data,” in this case by eliminating regulatory restrictions, fear to share data, or departmental politics which often stand as an obstacle in data projects. This is based on the fact that with data virtualization you don’t need to move data from where it resides “physically” as data is not really taken out of the source applications.
If you are asking for ingredients to make a fast recipe then data virtualization can help with its fast querying across data sources:
Data virtualization knows your ingredients -“data”- and where they reside quite well, such as number of processing units and partitions. It even knows key ingredients’ sources like Apache Spark and Hadoop. You can run dynamic queries and instead of doing ETL and querying all your ingredients -“data”- from one source, you can query ingredients -“data”- across several data sources with great performance. If your organization currently uses multiple BI and data visualization tools, each with a different presentation layer, data virtualization can help in pulling/reading the data and also in connecting with legacy data systems and big data ones like Spark.
Easier to search for each ingredient “data” and “metadata” in the pot and know how they are mixed or related to each other in the recipe:
If you are not an expert chef (i.e. technical user), but rather a business user who wants to make a good recipe, you can use data virtualization to see what’s inside the pot by searching for your data and metadata in a google-like way. You can also build a recipe of a virtualized layer for a small set of functionality in a matter of weeks.
Always get fresh ingredients -“data”:
Data virtualization provides real-time raw data access. The data continues to reside in the source database, so it does not become out of date during the access process.
This was a quick story on how data virtualization could help get a magical soup stone. If you are interested in knowing how the magical soup stone and other technologies can help you become data-driven, follow my blog for more posts.
Feel free to share your recipes for other great big data cuisines in the comment section below!
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