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 is Considered Independent Technology
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.
Interchangeable With the Data Warehouse
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.
Delivers Insights On Its Own
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. Businesses need access to the right software and hardware toolkits, as well as the right type of professional talent in order to fully realize all the benefits of the data lake.
Hard to Work with Multi-Format Sources
A concern among users of the data lake is that storing data in multiple formats leads to most apps not being able to utilize the various types of data simultaneously. Most apps support only a handful of the mostly structured data types, thus limiting the user’s possible data types and sources. Businesses that build and use data lakes tend to also create data services. These data services are virtual files that link to one or more data analysis processes instead of actual files. Each process can then apply more complex security policies and regenerate expired data.
Cloud-based Data Lakes Are Not As Secure As Believed
A cloud-based data lake is designed with security in mind. Businesses should take a range of security measures when building and running the data lake in the cloud. Two security measures to look into are data anonymization and encryption.
Data anonymization is highly recommended when large amounts of data are stored in one place. It is beneficial to only anonymize certain sets due to the fact that anonymization requires data-specific implementation. Recent adaptations have provided simple ways to encrypt data in transit and at rest. Software is able to encrypt an entire data lake instead of bits of data at a time.
Only Usable by Data Scientists
A data lake doesn’t have to be used only by scientists. It can be used by any business team that collectively has the skills needed to operate one. Maintaining the data lake requires individuals who know the various sources of data available, can acquire access to these data sources, and has a good understanding of available tool sets used for the analysis of disparate types of data.
Using a data lake creates the ability to develop better decision-making skills, better services, accelerated growth, and will pave the way to new insights. It has the potential to revolutionize strategic initiative within businesses. Building a data lake isn’t complicated and definitely worth the benefits. Data lakes will soon be used more and more in the future and businesses that get a head start can reap the advantages early on.
