There was a time not long ago that words like “artificial intelligence” brought to mind human-like robots and mega-computers out to take over the world. Today, artificial intelligence, known as AI, along with machine learning (ML), the Internet of Things (IoT), and Big Data, are becoming “business as usual” for an increasing number of companies.
They’re driving innovation, creating efficiencies, generating new products and services, and opening the door to entirely new business models. It’s all because of data — or rather what we can do with data.
The Challenges of Big Data Projects
Making the most out of data, however, requires more than a few data analysts on staff. You have to be able to capture or gather the data, store it, process it, and search for it, as well as share it, transfer it, visualize it, and more. It requires specific solution architecture, immense processing power, and infrastructure to support it all.
There are also lots of decisions to be made and variables to consider that can affect your solution design. Will you set up a server or distributed cluster for parallel computing or is cloud computing the way to go? Is your primary datastore a relational database such as PostgreSQL or MySQL or a NoSQL database like ElasticSearch, MongoDB, or DynamoDB?
Is your data structured or unstructured, or do you have both? Will you need to build a data warehouse or a data lake, or possibly both? If you’ll be dealing with streaming data, will you employ stream processing or batch processing? Will data privacy requirements affect your projects such as those associated with HIPAA and PCI DSS? The list of questions goes on, and it can be overwhelming.
The Case for AWS
So how do you make sense of all that’s involved in a cloud Big Data solution and get one started? One solution is to work with a company like Amazon Web Services (AWS) which offers a wide range of tools, technologies, and frameworks specifically for cloud Big Data solutions, including those that entail IoT, ML, and AI. As helpful as these resources are, however, there’s still a learning curve involved when using them. You may not have the luxury of that time. Plus, you may not have the staff resources to devote to a Big Data-type project. That’s why teaming up with a consultant with broad-based expertise in cloud Big Data projects and AWS services may be the way to go.
The problem is that those experienced consultants aren’t easy to find. There are many companies that design and implement IoT solutions. Others specialize in machine learning applications. Still, others focus on cloud migration. But there aren’t many that have a range of experience and expertise that covers most everything you might need in developing and deploying a Big Data solution — particularly using AWS tools. ClearScale is one of the few that does.
ClearScale and Big Data Projects
As an AWS Premier Consulting Partner, ClearScale has expertise working with AWS Cloud services and a wide range of tools and technologies. That includes Amazon Aurora, a MySQL/PostgreSQL compatible database engine; Amazon EMR (Elastic MapReduce)/Amazon Glue for processing data from external sources using Hadoop/Spark; Amazon Kinesis to consume and process data with real-time streams; Amazon Redshift for a fast and powerful cloud-based data warehouse; Amazon S3 for analysis, backup, and content data storage; AWS Lambda to run code without provisioning or managing servers; and others.
Our team also regularly works with open-source and enterprise cloud Big Data solutions including Debezium, Apache Kafka, Apache Hadoop, Apache Spark, Cassandra, and MongoDB.
Plus, ClearScale has earned AWS competency designations in several areas, including migration, DevOps, data and analytics, and IoT. We also have extensive expertise with high volume, variety, and velocity Big Data projects that include the use of AI, ML, and IoT. These aren’t standard projects that use off-the-shelf solutions. They entail highly customized solutions. Among them:
- Recommendation engine for high-volume transaction processing, data consumption and storage, analysis, and creation of recommendations
- Big Data Internet of Things system to enable speedy processing of incoming data from an IoT company’s home automation devices
- Internal business analytics platform for an online curriculum solution using Amazon Redshift and Kinesis
- Self-service portal to create custom demo environments for a SaaS customer’s insights and analytics platform
- Machine Learning platform for predictive analytic modeling of consumer credit behavior
- Large AWS Data Lake for Analysis of Heterogeneous Data
Get Ready to Harness the Power of Big Data
If your company is considering launching a Big Data project, consider teaming up with ClearScale to make it easier. From the infrastructure to power your project to app development, ClearScale delivers the expertise you need.