AI Data Analytics
Learn how to prepare your organization for an AI transformation to drive tangible business value.
Benefits
Our approach
CBTS solutions
Receive personalized, expert guidance with our proven methods.
Readiness Workshop
Readiness Assessment
Readiness Remediation
Deployment
This quick, 1-day workshop leads your organization through a series of discovery exercises to determine a high-level path forward for a successful AI implementation. Topics discussed include:
- Goals for using AI.
- Pain points that AI can address.
- Current capabilities related to AI.
- Data strategy in place that meets your risk tolerance.
- Necessary infrastructure and resources for AI.
Deliverable:
- Preliminary Assessment Results.
- Data protection and restrictions.
- Data structuring.
- Secure user access, from anywhere on any device.
- Secure applications with access to data.
Deliverables:
- Detailed Readiness Assessment.
- AI Readiness Gap Report.
- Over-exposure of data.
- Overprivileged and risky users.
- Device risk.
- Discovery and control of AI apps.
Deliverable:
- Detailed Remediation Report.
- Pilot launch.
- Assigning licenses to end users.
- Adoption and Change Management Training.
- User training.
Deliverables
- Rollout plan and implementation for organization.
Overcoming privacy and security barriers to generative AI adoption
Meeting the pace of big data growth
To manage the influx of data while navigating modern technologies and tools, companies must consider hiring skilled professionals, such as data scientists, analysts, and engineers. However, the rapid evolution of data tools often outpaces professional development and many organizations are left struggling to bridge the gap.
CBTS has extensive experience consolidating data from applications, disparate platforms, and websites into cloud-based storage solutions, such as data lakes. The deployment process is swift and highly customized, leading to a faster value realization.
BIG DATA ANALYTICS
What are big data analytics?
Managing data across disparate platforms can be difficult, especially when saved in a format only specific software can read. This can cause issues for on-premises data storage systems, which can’t always keep up with the amount of generated data.
Cloud-based data lakes emerged as a solution offering a way to manage and store data across multiple platforms in a more efficient way. Users manage their data to create business intelligence reports, track analytics, and generate custom dashboards accessible from anywhere. The consolidated data can be analyzed and manipulated using AI and machine learning
BENEFITS
Benefits of big data analytics
Cloud-based data lake solutions
Remove cost of expanding or upgrading data resources and management.
Grow with your business
Massive scale and growth of unstructured data.
Value
Data-driven business decisions to accelerate growth and gain a competitive edge.
Accessible anywhere
Real-time demands for usable information and insights.
More profit
Increased revenue and customer satisfaction.
Variety
Variable data in different formats, including e-mail, social media, and video.
New opportunity
Data that unlocks new business opportunities.
%
of large companies reported that they are achieving returns on their data and AI investments.
Sloan Review
OUR APPROACH
Why CBTS?
Data lakes provide a future-proof solution that can scale to almost infinite levels while keeping costs low, thanks to the power of the Cloud. Your investment will continue to provide value as cloud tools and machine learning advance.
CBTS is the go-to expert in deploying data lakes. Our engineers are experienced in leveraging storage best practices to optimize your data, ensure your data is always encrypted, and maximize the speed of search and retrieval. Trust us to make your data lake a valuable asset for years.
“By centralizing data in one place, clients can gain insights and make better decisions. But it’s important to partner with someone who can ensure proper governance to avoid potential security and privacy risks.”
-Brian Quinn, Senior Vice President of Business and Product Development
CBTS SOLUTIONS
CBTS big data analytics solutions
Managed cloud-based data lakes allow secure access and scalability.
Using data lake architecture in the Cloud eliminates the drawbacks of storing data on-premises. Using a cloud-based system lets clients save on the expenses of constantly expanding or upgrading data resources and management. With data lake storage, companies can scale elastically, paying only for the storage and services they require in a pay-as-you-go approach.
Assess
Define
Execute
Improve scalability, performance, and security. Test and validate data lake functionality with predictive analytics for improved decision making.
Monitor
Monitor, maintain, and update the data lake for reliability, security, and evolving organizational needs.
Security is of the utmost importance when it comes to a data lake. CBTS values the confidentiality, integrity, and availability of data, and we take all necessary measures to ensure that our clients’ data lake is secure.
Aligning big data analytics with business objectives
The purpose of data in a company should be to advance business goals. To achieve this, it’s essential to create a strategy for collecting, organizing, and utilizing data aligned with the company’s objectives. The key is to look beyond the current role of data within the company and aim to harness its full potential in order to achieve business goals more effectively. It should possess the capability and depth of insights to give you a competitive edge and become a disruptor in your industry.
Data is the most valuable raw material today… For this reason, data-driven businesses must pay special attention to only feeding their analytics systems quality data.
Forbes
FAQs
Top 5 questions
What is a data lake?
It’s a large and centralized repository that stores structured and unstructured data at any scale, allowing organizations to store and process vast amounts of data in its native format.
What are the benefits of using a data lake for big data analytics?
Data lakes enable storage and processing of large volumes of data at a low cost, the flexibility to handle different types of data, and advanced analytics and machine-learning algorithms.
How does a data lake differ from a traditional data warehouse?
A data lake stores raw data without preprocessing or organizing it. It can transform and analyze data later as needed and manage unstructured data, unlike a data warehouse.
What are some common uses for data lakes and big data analytics?
Various industries use data lakes and big data analytics for customer analytics, fraud detection, predictive maintenance, and supply chain optimization.
How do data lakes ensure data security and privacy?
Data lakes can ensure data security and privacy through access controls, encryption, and data masking. Additionally, data lakes can be integrated with existing security and compliance tools to ensure regulatory compliance.
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