<img height="1" width="1" style="display:none;" alt="" src="https://px.ads.linkedin.com/collect/?pid=1232938&amp;fmt=gif">
redapt - rack integration - white icon
Data Center Infrastructure

Enhance your data center infrastructure with tailored solutions that boost performance and efficiency, ensuring rapid growth and exceptional customer experiences.

redapt - data estate assessment - white icon
Cybersecurity

Fortify your operations with comprehensive cybersecurity solutions that deliver resilient protection and end-to-end risk mitigation.

redapt - cloud adoption ready - white icon
Managed Cloud Services

Align your cloud strategy with your business objectives through our end-to-end managed services, delivering expert oversight across infrastructure, data optimization, and cost control.

Cloud_Adoption
Cloud Adoption

Adopt the cloud confidently with expert guidance on capacity, cloud-native technologies, and a step-by-step path for successful migration.

redapt - devops adoption - white icon
DevOps

Energize your software development lifecycle with tailored DevOps to match your needs and workflows.

redapt - data science experiment - white icon
Data Analytics

Successfully adopt advanced analytics capabilities to unlock insights, inform the design of your products, and make smarter decisions.

Artifical_Intelligence
Artificial Intelligence

Leverage Artificial Intelligence to generate actionable insights, uncover new revenue opportunities, and drive more informed decision-making.

Application_Modernization
Application Modernization

Modernize your applications with advanced development methodologies, driving greater agility, efficiency, and continuous innovation to excel in today’s competitive environment.

BLOG
The latest in infrastructure, technology, and security

From emerging innovations to real-world applications, we cover what helps leaders navigate complexity, drive transformation, and make smarter decisions in a rapidly evolving landscape.

VIDEO CENTER
Go deeper with expert stories, insights, and strategy

Your destination for expert conversations, client stories, and diving deep into the latest in infrastructure, technology, and business strategy.

CUSTOMER STORIES
Discover how we elevate organizations

Read some of our customer stories to learn more about how we develop and implement solutions, along with how those solutions have helped our clients and partners.

KNOWLEDGE CENTER
Stay informed with expert guides, trends, and webinars

Explore our curated collection of eBooks, guides, and webinars designed to help leaders stay informed and ahead of trends.

redapt-employee-unboxing-tech
ABOUT US
Get to know our mission, team, and what drives us

We specialize in implementing and managing technical solutions to support your infrastructure and digital environments. 

RC_DC_6481
LEADERSHIP
Meet the leaders driving innovation and customer success

Bringing together decades of experience in technology, business strategy, and customer success.

What the company needed Image-1
CAREERS
Join a team built on impact, collaboration, and growth

Build lasting relationships and deliver real-world results.

Actionable Insights.

Make-or-Break Focus Areas.

Experts Save You Time.

Let our experts save you time, money, and stress as you explore solutions. Talk to an expert today!

Contact Us

  • There are no suggestions because the search field is empty.
Banner Bg Image

How to Get More from Data Science

The flood of data now available to enterprises is fueling a revolution in data science.

What was once relegated to spreadsheets can now involve advanced technologies like artificial intelligence (AI), machine learning (ML), and deep learning—powerful tools for unlocking insights, surfacing efficiencies, and informing the creation of new products.

As companies look to build out their data science capabilities, however, many of them encounter the same question: How do you actually get the most bang for your data science buck?

As you know, storing and analyzing vast amounts of data can be an expensive proposition. This is especially true when you’re leveraging tools like AI and ML. And when you take into account the reality that the majority of advanced analytics models rarely make it to production, the idea of investing in data science can become even less appetizing.

The good news, though, is that there are steps your business can take to successfully increase your data science capabilities without blowing holes in your budget. 

data-magnifying-glassStep 1. Focus on your data

Any data science project is only as good as the data it has access to, which is why your first step toward increasing your data science capabilities should be to focus on the data you have.

In general, there are three areas you should focus on:

  1. Assessing your data to understand what it is and where it’s coming from. This means combing through all your current analytics workloads and data sources, examining the completeness and accuracy of that data, and identifying which of your teams needs access to specific data sets.
  2. Simplifying your data, which requires overhauling the way your data is distributed and your queries are handled. To do this, you need to spread your data in such a way that valuable data is not buried beneath a mountain of useless information.
  3. Warehousing data so your data scientists have a substantial playground in which to run models. The benefits of data warehouses include ease of access to critical data for your teams, an accelerated turnaround on analysis and reporting, and ensured governance and security across the board.

speed-dataStep 2: Democratize your data

For years, data was under the control of IT gatekeepers. 

Now, as more and more enterprises look to leverage data science and advanced analytics, there is a greater push to democratize data so it is accessible to everyone from analysts and executives to marketing departments.

In other words, when it comes to data science, the actual scientists are only one spoke in the wheel.

While assessing, simplifying, and warehousing your data are critical components to democratization, there are additional tools available to make information available throughout your organization. Tools like:

  • Data virtualization software for manipulating data regardless of inconsistencies, file formats, or data location
  • Data federation software that leverages metadata to aggregate information into a single virtual database
  • Data lakes to centrally locate information and partition it out for access

cylinder-data-storage_iconStep 3: Break down silos

The chasm between those data science models that are being created and those that actually reach production can be attributed to a number of things. These include the relative newness of advanced analytics technologies and a lack of skills with specialized software.

The most common culprit, however, is a disconnect between data science teams and IT teams within an organization. And driving this disconnect is the fact that most models built by data scientists are done so on dedicated workstations or cloud instances that IT teams don’t actively manage. 

This means that when it comes to actually moving a model from the workstation or cloud instance into production, IT teams are routinely in the dark about how to deploy that model at scale.

The aforementioned data democratization can go a long way toward bridging this gap. But if your organization is just getting started on building out your data science capabilities, our ML Accelerator program can help take you from zero to production ready with ML models quickly.

Included in the ML Accelerator program is a ready-to-use platform and infrastructure featuring:

  • Kubernetes based on Rancher
  • Hardware to support ML and deep learning (DL) workloads, including a base model with 4xA100 GPUs
  • Workflow management with Kubeflow and ready-built containers
  • Self-service Jupyter notebooks for data exploration
  • Integration with Nvidia RAPIDS and Spark
  • IT monitoring and alerting with Prometheus and Grafana

Beyond the platform, the program also includes engineering assistance to help you build and deploy your first model, a workshop to kickstart your data science projects, and best practices for building out models successfully.

To learn more about our ML Accelerator program, contact one of our experts.