Big Data is creating great opportunities in the enterprise, but it can also create challenging integration issues. The world created 170 zettabytes in 2015 according to IDC. This shouldn’t come as a surprise since we create about 2.5 quintillion bytes of data a day, can you imagine how much data is out there today?
Big Data can hold any data source in any format
If everything is perfect then what’s the problem?
It’s true, Big Data is also scalable, not only does it accept any type of data but there is no limitation to the amount of data you can store. However, there are some drawbacks to this.
Storing everything without organization can be dangerous; it’s critical to know upfront what is important data and what’s not. If not, things can get messy rather quickly in your Data Lakes.
After Setup Big Data is not as easy as Imagined
Once you’ve added all your data sets into your Big Data store or lake, you’re not able to simply access it as imagined. Your data must be cleansed and organized first, in a way that is easy to understand for end users. Once the data is cleansed, then you can expose it through an API (which bring us to our next challenge).
Can’t access your data without 3P tools
In order to retrieve your data from Big Data stores or lakes you will more than likely require a 3 Party tool. You guessed it, this leads to another set of considerations, is the API easy to use with your current Big Data repositories and does it do the bare minimum, security, governance, and data preparation?
Requires Time & Development
One of the goals of Big Data is to save money by providing an alternative solution for costly data warehouse upgrades by taking some (if not all) the load and using a less expensive solutions such as Hadoop.
Have you thought of leveraging Analytics with EE BigDataNOW™?
In response to the overwhelming variety of data that enterprises encounter, many NoSQL databases were created, the most popular of which is Hadoop. The collection of open-source projects centered around distributed data processing can analyze large sets of unstructured data. Hadoop has given new competitive advantages to companies, allowing them to store data and analyze it later.
So what happens when the data analysis becomes more complex as the data grows, or operational data must be bridged with other external/business data? As the analytic capacity grows, so does the infrastructure and workforce costs; keep that in mind when considering your Big Data integration.
Have you thought of leveraging Analytics with Enterprise Enabler®?
Performing the analysis to get these insights is only the first step in taking advantage of the benefits of Hadoop and Big Data.
When you combine the power of Enterprise Enabler (EE), in conjunction with the AppComm™ Technology such as Hadoop AppComm, you can create a virtual database which eliminates the need for a traditional warehouse altogether (reducing infrastructure and workforce cost). EE BigDataNOW™ is specific to Big Data, it will connect instantly with Hadoop and operational data. Once connected, you can use SQL or a BI Tool of your choice to query the data. This approach requires no schema change and can be implemented in days instead of months/years with a traditional Data Warehouse approach.
EE BigDataNOW™exposes your integrated data as services to consuming applications – BI reporting tools, dashboards, flat files, web applications, mobile applications, etc. – making it easy to turn the analytics results into actionable information that can be used by the business stakeholders.
So scalability and limited workforce won’t be a challenge.