Pace Tech Fellow Blog

Stay up-to-date on the newest in Tech:

How to stand-out as a job-seeker, employer, and Higher-Ed decision maker in the everchanging Tech industry

Our Blog

Visit our blog for breaking updates, trends and breakthroughs sourced from the best that the continuing education landscape has to offer.

Blog Img

Data Science

  1. How long does it take to learn data mining

    How Long Does it Take to Learn Data Mining?

    Categories: Data Science

    Discover the timeline for mastering data mining and the essential skills needed for success in this dynamic field.

    Read more
  2. why predictive analytics is the future of data

    5 Reasons Predictive Analytics: Shaping the Future of Data

    Categories: Data Science

    Discover the future of data-driven decision-making with predictive analytics. Explore five compelling reasons why predictive analytics is reshaping industries.

    Read more
  3. Data visualizations that employees understand

    4 Powerful Data Visualizations that Non-Data Employees Understand

    Categories: Data Science

    Unlock the world of data insights with our blog on four powerful data visualizations tailored for non-data employees.

    Read more
  4. How should data science and AI work together

    How Should AI & Data Science Work Together?

    Categories: Data Science , AI & Machine Learning

    AI and data science can together provide more insight into how your organization should collect data, cleanse that data, and derive meaningful insights from that data which drive more informed operations.

    Read more
  5. Data science strategies your company should consider

    4 Data Science Strategies Your Company Should Consider

    Categories: Data Science

    Consider data science strategies in AI-driven operations, prioritizing data security, cultivating a data-driven culture, and combining data science and analytics for a wider approach.

    Read more
  6. Four things your team might get wrong about data visualization

    4 Things Your Team Might Get Wrong about Data Visualization

    Categories: Data Science

    Analysts can lack clarity in their analysis processes, overly focus on design over function, forget to consider context, and over-rely on automation when implementing data visualization.

    Read more
  7. Strategies to improve data cleaning and transformation

    6 Strategies to Improve Data Cleaning & Transformation Efficiency

    Categories: Data Science

    Validate your information, define your project’s scope, document the strategy, implement automation, and create data quality metrics to improve your organization’s data cleaning and transformation process.

    Read more
  8. Priorities to keep in mind when building a data warehouse

    4 Things to Keep in Mind When Creating a Data Warehouse

    Categories: Data Science

    Building a data warehouse is a critical responsibility for any company that wants to make informed decisions based on data. A data warehouse is a repository of integrated data from different sources within an organization. It allows companies to analyze large amounts of data and make data-driven decisions. For example, a data warehouse can inform a company about customer behavior, sales trends, and inventory management. With this information, a company can make more informed and efficient decisions, leading to fewer errors and better outcomes.

    To build a data warehouse, several things need to be kept in mind. A data warehouse needs to be designed to meet the unique needs of a company, taking into account its specific goals and objectives. It requires a thoughtful approach to ensure that it is effective and efficient in its purpose. Below, we will identify four priorities to keep in mind when building a data warehouse.

    How Do I Build a Data Warehouse?

    Building a data warehouse requires careful planning and execution. It is a complex process that involves many different factors. To ensure that your data warehouse is effective and efficient, there are several things that you need to keep in mind. Below, we will identify four priorities to keep in mind when building a data warehouse.

    Priority #1: Define the Purpose of Your Data Warehouse

    Before starting the construction of a data warehouse, it's crucial to define its purpose. Determine what data you will collect, why you will collect it, and how you will use it. Understanding your goals and objectives is critical in designing an effective data warehouse. With a clear purpose, you can ensure that your data warehouse is designed to meet your specific needs.

    Once you have defined your purpose, you can then decide what data sources you will use to populate your data warehouse. Data can come from various sources such as CRM systems, ERP systems, social media, website analytics,

    Read more

One education platform to replace them all.

Explore the best online curriculums, bootcamps and certifications, backed by a responsive Career Services team, industry-leading experts and flexible payment options.

Contact our Admissions Team

We’re on a mission to inform and inspire a new generation of educated students. We’ll help you pursue a rewarding career of your choice, through mentor-led bootcamps engineered to help you succeed in your field. Equal parts flexibility, support and academic rigor, Pace offers an elevated approach that entirely redefines self-paced education.

Talk to an Advisor