What Most People Get Wrong About Data Lakes
The technology industry has continued to find new ways to interpret big data, to develop artificial intelligence, create backup solutions, and expand the cloud into a platform for businesses. One issue that many businesses face is trying to find ways to make data analysis easier in order to deliver faster and more insightful results. A data lake has helped businesses accomplish this. The data lake has become a popular big data tool due to its ability to support the accumulation of data in the original format from a potentially infinite number of sources. These sources include such diverse sources as social media, ticketing systems, and automatic sensors.
The data lake is still a relatively new addition to the technology industry. Since it is still developing, there are often a large amount of misconceptions about what data lakes are and how they work. Below are the top six misconceptions.
The data lake supports the big data endeavors of businesses by creating a path to the discovery of brand new insights. Many users would describe the data lake as another technological tool, but it can be more precisely defined as the aggregating of old tools. This misconception comes from the realization that processing data of various types and formats in one place enables new found data manipulation techniques to be combined.
The data lake is not the first to try and accomplish concentrating data from different sources for correlation and modeling purposes. Data warehouses have been working on combining data for years. Although both are trying to accomplish the same thing, due to their different types of focus on data structure, usage, and data size they are two very different concepts. The data lake is more suited to analyze both structured and unstructured data compared to the data warehouse.
Like most data software, the data lake needs to be used by professionals who understand the reality behind data storage and business processes. The data lake works best when used with a combination of processing, interrogation, transformation, and visualization tools.
