5 Must-Have Tips for Jumping on Board the IoT Train
The IoT is here, both in industry and in the consumer sector. Not only is the IoT a fantastic way to connect with and offer value to your customers, it is also a rich resource for data. If your plans involve big data and the IoT, these tips are for you.
1. The Data Storage Infrastructure Has to Come First
Will you use a data warehouse or a data lake? Is Hadoop your best choice, or another big data solution? Know how you’ll manage the vast quantities of data that the IoT brings before you begin the project.
Businesses that successfully leverage the IoT don’t even consider what data to collect and how until they figure out the infrastructure they will use to store and process the data. For instance, if you plan for streaming to be a part of your strategy, you will need to set up an infrastructure that will allow for that type of fast processing. You will also need to establish a data warehouse or data lake that is capable of handling large volumes of semi-structured or unstructured data.
2. The Data Capture Has to Be Seamless
IoT devices that make it difficult or time-consuming for users to enter their data simply won’t be used. One of the tricks is to develop connected devices that capture the data without any human input or offer enough value to the user to make it worth their while to regularly and consistently input the data you need to collect.
3. The Organization Has to Clearly Define Goals for the Project
Your goals for the IoT have to be clearly defined before you begin the project, or it will stray off course early and steeply. Big data and data analytics are enormous undertakings even with a sound and well-defined strategy and goals in mind. Without these compasses, the project is doomed before it begins.
4. The Organization Has to Have the Right People on Board
That data scientist might not be as far away as you think. Data scientists have a skills set that can easily be developed in house.
Don’t let all of the talk about how difficult it is to find a qualified data scientist scare you away from pursuing your big data goals. Yes, it’s hard to hire a data scientist off the street and to keep one once you’ve found him or her. But it isn’t as difficult as you might imagine to develop your own data scientist (or a data science team) on your own. The hardest part of this initiative is keeping those valuable people once they’re trained and get some experience.
5. Don’t be Creepy About It
When done right, IoT devices are a useful, practical, welcome part of the users’ lives. When done wrong, it’s just flat creepy. Be careful about the types of data you collect and how you use that data. If users get the feeling that you’re doing more spying on them than you are delivering value to their lives, you and your device will be history.
Are you ready to get the Big Data solutions you need to leverage the IoT?