This is the era of big data analytics. Data-driven decision-making is not an exception anymore – it is a norm. Yet, around 80% of the data generated by businesses are dark data – they remain unutilised. And a significant portion of this dark data is generated by IoT devices. Since 90% of IoT data is unstructured, it becomes challenging to make sense of it using traditional analytics tools. This is where Aceso Analytics comes in. We specialise in IoT data analytics on edge, standing on the shoulder of cloud computing and Data Warehouse. Empower your business with our comprehensive expertise in the NoSQL database paradigm and manipulate unstructured IoT data precisely the way you want.
IoT data analysis comes with a set of challenges that need to be addressed for organisations to benefit from it. Here are the IoT big data challenges that Aceso Analytics addresses:
80% – 90% of enterprise data generated today are unstructured. (Source MongoDB)
You can’t fit such data into any traditional Relational Database system. Some IoT data come in the form of semi-structured data. Here again, there is no standard method of collecting such data. You have to convert semi-structured data into a machine-readable format. Manipulating such unstructured data is challenging.
IoT data comes in many shapes and forms. Take, for example, a basic IoT setup in homes – a motion detector, a light sensor, a temperature sensor and a voice recognition sensor. Each of these sensors generates different types of data. Combining this heterogeneous data to provide comprehensive and relevant services is highly challenging.
On the one hand, IoT devices generate a wide variety of data, and on the other hand, these devices can generate vast amounts of data per second. For example, Uber has 1500+ TB of data that it needs to query on a real time basis. Analysing such a massive amount of heterogeneous data on a real-time basis is a Herculean task.
Storing and organising such a massive volume of heterogeneous data for future use should be taken seriously. Yes, there are Data Lakes and Warehouses to help us. But without a strict vigil, haphazard storage of IoT data can turn your Data Lake into a data swamp in no time.
Aceso Analytics provides an end-to-end IoT data analytics solution empowering your business to tame big data and make data-driven decisions.
With our in-house Machine Learning models, we enhance your existing Data Analytics infrastructure with the power of NLP, empowering your organisation to make sense of the huge text-based data coming from IoT sensors. Aceso Analytics combines structured (SQL) and unstructured (NoSQL) data with database tools like MongoDB. For static sensor-based data analytics, we offer Spark-based analytics services as well.
IoT data is Spatio-temporal in nature. Our Data Scientists at Aceso Analytics have expertise in performing complex joins and merging structured and unstructured data. Not all IoT data is entirely unstructured. If you look closely, much of IoT is actually semi-structured, having non-standard patterns. Aceso Analytics has the bandwidth to transform these non-standard data patterns into machine-readable formats.
The problem with IoT is that the massive amount of heterogeneous data results in poor real-time data processing. The solution to this problem is edge analytics. We build bespoke IoT analytics tools that reside near the origin of data (i.e. IoT devices), enabling us to minimise data transfer and analyse data right where the device is. Once the analysis is done, the aggregated result or the anomalies are sent to the cloud – saving a lot of back-and-forths.
Aceso Analytics builds end-to-end automated data ingestion pipelines armed with parallel processing and indexing features enabling businesses to extract IoT data seamlessly. Along with the traditional batch extraction of data, we have expertise in building event-based data transfer systems by taking advantage of cloud tools like Azure Event Hub and AWS IoT events.
Aceso Analytics has extensive expertise in building custom data lakes with all the best practices in place. We believe that dumping data in a haphazard manner is a sure-shot way toward failure. We guide you in building a stable and organised data lake with partitions and metadata, ensuring streamlined access to IoT data.
To make data-driven decisions, you need to have both a bird’s-eye view and a closer look at the IoT data. However, it is not humanly possible to parse millions of rows of data to find insights. Our data visualisation solution enables you to find hidden insights buried deep within your big data enabling you to make the right decision backed by data. This can be your ultimate differentiation strategy.
Maintaining the security of data is a legitimate concern when it comes to IoT. IoT data originates in a different location and gets sent to another location. This can result in security and compliance issues.
Aceso Analytics is a fully GDPR-compliant organisation protecting your client’s data as per the guidelines laid by the EU. We take every measure to protect user data using military-grade encryption and confine it within the EU. Our cloud engineers remain vigilant 24/7 and keep the cloud workload secure by adhering to all the security best practices pertaining to AWS and Azure.
The future is here. The future is IoT. If you are not collecting and analysing your IoT data properly, all your Data Analytics endeavours will remain incomplete.
Contact Aceso Analytics and hear what your IoT data has to tell you!
Learn more about how we can help you and have your questions cleared.