Data of any volume, variety & velocity
Big data & data engineering
Name it, google It and put the word “SMART” before. Nowadays everything is getting “SMART”. Meaning that every machine, gadget, household equipment, asset, … has sensors. This requires new technologies to be able to handle these large volumes of data that come in, in different speeds & different formats. Above that, if it aren’t sensors, maybe we are talking about website statistics, log data, … This data explosion has caused us to rethink technology and fit this into our data & analytics architecture.
What is Big Data & Data Engineering?
A lot of prominent thought-leaders have tried to grasp this in a few words or sentences. However, where everyone finds a conclusion from a technology perspective is that it is about handling data that can’t be handled (or less efficient) by the traditional relational database management systems. Think about the large SQL Databases. From a business perspective this also gives a lot of advantages that enables new business uses cases.
Why do we need Big Data & Data Engineering?
That is a good question. Typically this is followed by: “My SQL Database can also store large amounts of data.”. The reflex behind this questions is good, however it comes with some limitations.
Some reasons why big data & data engineering are becoming more and more important:
- Storing large objects of data in a relational database is expensive
- Big data technologies do not force the source data to fit in a specific format. You only define the schema of the data when you need the data. This means you define your schema-on-read instead of the traditional schema-on-write
- Storage can be separated from compute. Meaning you only pay for the most expensive part (the compute) when as you need it & when you need it.
- Have we already mentioned that the storage is cheap!? Depending on the use case ranging from archiving to ultra fast premium storage you can already start with storing Terabytes of data for a few Euro per month.
- Data Engineering tools speak more languages! Let’s talk Python, R, Scala, … and even SQL!
I hope you are as convinced as we are!
How to start with Big Data & Data Engineering?
I hope we already answered the “Why” pretty well. Now the next questions is “How?”.
This is a typical question we get quite often. The goal here is to put big data & data engineering in place so that it fit’s the already existing architecture. Or when starting from “carte blanche”, how can we be as future proof as possible. In both scenario’s the answer is the same we need to fulfill the business needs or add extra value from data. It is really a matter of mapping your data use cases on your technological architecture.
To give you an example: “You have a project in your data & analytics portfolio that needs to crunch large amounts of unstructured data every night?”. Use Big data technology! As another example: “You need to have an aging balance of your receivables from your ERP?”. Please use your traditional Data Warehouse.
We hope you understand it is a matter of using the right tool for the job.
How Lytix can help me with Big Data & Data Engineering?
If you are just making the leap towards getting the full potential from your big data or need extra guidance & assistance that is where we typically come into play.
We are at our strongest in collaborating towards the best architecture for your use case and also the hands-on implementation of the chosen technology. Meaning configuring the services & connections, writing the actual code to transform your data, … All the aspects to go from data to value using big data technology.
Moving from Excels towards trusted data
UNBURDENING IT & EMPOWERING BUSINESS
DATA OF ANY VOLUME, VARIETY & VELOCITY
BIG DATA ENGINEERING
AUTOMATING & OPTIMIZING DECISIONS
LET THE NUMBERS speak for themselves
DATA THOUGHT LEADERSHIP INTO PRACTICE
Big data is here and it is only getting bigger in the coming years! So organizations needs to get used to it to get the maximum value out of their data. As Lytix we are at our strongest in defining the architecture, configuring the components & code your transformations from data to value using big data technology!
Does this sound interesting to you? Leave your details below and get in touch so we can share you our Big Data & Data Engineering quick starter!