Before the end of the decade, the number of connected objects is projected to expand greatly. According to several different analysts, the number of connected objects by 2020 could be as low as 26 billion or as high as 50 billion. But even the low end of that range is quite large. Indeed, connectedness is becoming commonplace and accepted across a wide spectrum of services and applications.
The connected economy impacts both consumers and businesses, with the overall market for IoT technology projected to expand to $883.55bn by 2022. Businesses use sensors and connected devices to track inventory, survey the workplace, enforce policies, monitor clickstreams on web servers, and more.
Consumers wear devices to track their health and will increasingly enable more of their devices with sensors – both in their homes and in their automobiles.
We are at the advent of a society where just about every ‘thing’ (both living and inanimate) can have an attached or embedded sensor.
The impact of all these connected devices will certainly bring more automation and autonomy, but the IoT also heralds the creation of more data— a lot more data. IoT is projected to generate 400 zettabytes of data in 2018 alone. IDC’s Digital Universe study predicts that by 2020, the amount of information produced by the IoT will account for about 10% of all data on Earth.
This enormous growth in data creation is bringing about many important changes to IT and data management. One of the more significant struggles is brought about by the increased usage of non-traditional types of data. This includes unstructured data, streaming data, and different forms of database systems to handle the increased volume.
Although structured data remains the bedrock of the information infrastructure in most organizations, unstructured data is growing in importance. By unstructured data I mean things like images, videos, documents, e-mail and text messages, and really, anything that is not a traditional number or short character string.
It is important to note that unstructured data accounts for about 90% of all digital information according to International Data Corp. This means that new and different methods of manipulating and storing unstructured data are required because traditional methods used by legacy database systems don’t work very efficiently with it.
Streaming data is another important aspect of the connected economy. As connected sensors and devices are turned on, systems are needed to capture and read the generated data streams. But not every piece of data ever generated from a sensor may need to be stored for posterity. Instead, the stream of data needs to be ingested, filtered and analyzed, looking for patterns and anomalies. This can be done without ever persisting the entire stream of data—which will be increasingly important as the IoT grows and generates more and more data.
Additionally, new types of database systems that are being used are engineered for analytics and large data volume issues. NoSQL databases with their lightweight infrastructure and flexible schema capabilities are growing in acceptance and utilization. It is common for organizations to have multiple database systems, both relational/SQL and NoSQL. One specific type of NoSQL DBMS, the graph database system, focuses on relationships between values. Data is stored using graph structures with nodes, edges, and properties in a graph database. With graph database systems, the relationships between data elements are at least as important as the data itself.
Graphs are particularly useful when data elements are interconnected and there are an undetermined number of relationships between them. For example, graphs are ideal for maintaining a social network, like Facebook or LinkedIn. There are countless additional applications for graphs, such as routing and dispatching, public transportation links, road maps, and recommendation engines (such as those used by online retail sites).
And let’s not forget the privacy and security issues that will arise when everything is connected to everything else! For example, just this past April hackers were able to steal a database from a casino through an Internet-connect fish tank thermometer. Connectivity is the future, but we must be vigilant in protecting our connections and devices or suffer data breaches.
There are many additional aspects of connectedness and the data growth that accompanies it. Data protection, data governance and compliance, and metadata management are examples of significant areas that will be impacted by the IoT. And if it impacts data, it will impact the DBA and how data is managed and administered.
So, all you DBAs out there, get ready for the IoT!