Harness the Power of Your Data
Companies have access to more data than ever before, but many don’t know how to take full advantage. ClearScale equips engineering teams with the cloud infrastructure and tools they need to gather, store, and process data at scale, creating new sources of value along the way.
Achieve More With ClearScale and AWS
Deliver Better Offerings
Uncover valuable insights from your data and enhance your products and services accordingly to meet the unique needs of your customers.
Win New Business
Use big data to learn more about existing customers so that you can improve your sales efforts and grow your business.
Migrate your data to scalable, cloud-native data lakes that offer better performance at a fraction of the cost of commercial storage products.
Why Choose ClearScale as Your Data & Analytics Consulting Partner?
Comprehensive Suite of Data Services
ClearScale has earned the Data & Analytics Competency from AWS, validating our team’s ability to deliver real-world data analytics solutions through the cloud that drive positive results for clients. We offer a full range of data services, including analytics & data warehousing, data movement, data lakes, predictive analytics, machine learning, data cleaning, and data reconciliation.
In-depth Understanding of Modern Data Challenges
We understand what it takes to manage high volume, high variety, and high velocity data effectively. Our team has helped numerous businesses upgrade their data pipelines, repositories, and workflows to support disruptive applications and keep the data moving.
Our data analytics experts are experienced in AWS’s most common analytics services, including AWS Lake Formation, Amazon Athena, Amazon EMR, Amazon Redshift, Amazon Kinesis, AWS Glue, and more.
Common Data and Analytics Use Cases
Data Lakes & Warehouses
Build a data lake for collecting data, extracting insights from the data, and providing visualizations to share insights. Modernize, migrate, deploy, and operate Hadoop workloads, as well as transform data warehouse workloads.Read more
Use your data to train ML algorithms that enable personalized recommendation engines, predictive analytics, automation, and more. Modernize, migrate, deploy, and operate multi-tenant, multi-model enterprise ML systems.Read more
Gather massive volumes of data in real-time from IoT sources worldwide, and learn more about how your customers interact with your offerings. Deliver modern products for smart energy management, predictive analytics, and geo-aware ecosystems.Read more
“It took us less than a year to go from concept to delivery. We would not have achieved our goals as quickly as we did without ClearScale. We’re thrilled that we are able to launch a new product this year and begin benefitting from our investment so soon.”
- Karen Engstrom, SVP of Product InnovationRead Case Study
“We turned to ClearScale to design and implement a platform to capture and understand event-driven data coming out of our applications and business intelligence tools. ClearScale designed and implemented an ideal solution for us on time and under budget.”
- Richard Walker, CEO, Quik!Read Case Study
“Our engagement with ClearScale has been essential to achieving our goal of accelerating our data strategy. ClearScale helped us to build a new end-to-end data pipeline that will ingest all our data in real-time, giving us confidence that all of our data is in the right place, precisely when needed.”
- Scott Kinzie, VP of Marketing and Business Development, SmugMugRead Case Study
Frequently Asked Questions
What data infrastructure is available on AWS?
AWS offers a wide range of data infrastructure, including data lakes, purpose-built databases, data warehouses, analytics tools, data movement solutions, and services for leveraging AI/ML. With AWS data analytics services, organizations can easily ingest, store, process, and analyze massive volumes of data to discover new insights, inform decision-making, and launch valuable services.
What data management solutions are available on AWS?
AWS comes with many services across the data ecosystem areas mentioned above. Several of the most widely used AWS data analytics services include Amazon Athena for querying Amazon S3 data with SQL, AWS Glue for preparing and loading data in the cloud, AWS Lake Formation for quickly setting up secure data lakes, and Amazon SageMaker for creating, training, and launching machine learning programs at scale.
What are the benefits of using cloud-native data & analytics tools?
There are many benefits of using cloud-native data and analytics tools. First, the cloud offers virtually unlimited scalability, which means organizations can gather and use more data to support their goals. Many data cloud services also charge on a pay-per-use basis, freeing companies from having to pay for unused resources. Furthermore, with a cloud provider like AWS, organizations can integrate and streamline data management in one place, allowing developers to focus more on application development.
How can ClearScale help me harness the potential of my data?
ClearScale is an AWS Premier Tier Services partner with 11 AWS competencies. Our past work earned us the Data & Analytics competency, demonstrating our ability to plan and execute data-related projects on the cloud that generate tangible results. We understand how to build comprehensive data ecosystems on the AWS cloud according to the latest best practices and know how to bring our clients’ visions to life.
What is a data lake?
A data lake is a central location for storing both structured and unstructured data. In many cases, organizations don’t have defined purposes for data stored in data lakes, which differs from how leaders think about data warehouses. The raw information in data lakes is typically used by data scientists who want to run complex, yet flexible queries for big data applications. Data lakes tend to be most useful in industries that create a lot of raw data, like healthcare (e.g., clinical notes), logistics (e.g., contracts and forms), and education (e.g., LMS engagement data).
What data & analytics challenges do companies face today?
Some of the biggest data challenges companies face today include lack of scalable storage, growing sophistication of cybersecurity threats, and overabundance of diverse data types. Solving these challenges is difficult with legacy, on-premises solutions. Fortunately, AWS understands what organizations need to succeed in the big data age and offers powerful tools that make overcoming these issues easy.