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Data Science

  1. how to improve data literacy

    5 Ways to Improve Your Company’s Data Literacy

    Categories: Data Science

    The importance of data literacy has become increasingly blatant in recent years — primarily due to the damage that data illiteracy is causing.

    Data literacy allows organizations to learn from the data they collect, and implement growth strategies that create opportunities for success. By contrast, companies with high levels of data illiteracy are unable to learn from their own information. This makes them ill-prepared for change, and unable to adapt in the face of a market shift.

    Today, data literacy is often one of the biggest factors that separates transformative companies from organizations that fold in the face of change.

    What is data literacy?

    Data literacy is the ability to read, understand, analyze, work and communicate with data in its relevant context. Today, data literacy has quickly become a non-negotiable skill in many fields — including business.

    Modern companies compile data faster than ever before: 90% of the world’s data was created in the past two years alone. On a daily basis, your ability to access, consume, and interpret data grows more important.

    Data literacy is available to every business of every size. What was once a benefit has become a necessity: regardless of your company’s size, you need data literacy to improve operations, accelerate decision-making and draw powerful conclusions from the information you collect.

    How can I implement data literacy at my company?

    Teaching data literacy was once a university responsibility. Today, there are better ways to learn data collection, data analysis, and other critical skills that can improve data literacy across your organization.

    Here are five powerful ways to improve data literacy in your company.

    1. Establish clear leadership

    Employees rely on their leaders to provide direction, support

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  2. hiring the right data science team

    Your Guide to Hiring a Data Science Team

    Categories: Data Science

    As your business begins to scale, you may find yourself in need of additional data science resources, and team members. This isn’t always an easy process — how do you know who to trust with your company’s information and network? And how can you be sure that they will be the right fit for your organization?

    In this article, we’ll outline best practices for hiring the right data science team to complement your operations. We'll also help you understand what to look for, and how to make sure that your new data science team can help contribute to your overall goals.

    Why do I need a data science team?

    The first step in hiring a data science team is to identify your internal data-related needs. Do you need someone to manage your company’s data? Do you need help with migrating your information from one data collection platform to another? Do you also need help in collecting that data, or in applying strategies that help you derive meaningful conclusions from the data you collect?

    Do you need a specialist, or specialists, who can manage or optimize, your entire data science process for you?

    If you're expanding your business, changing your business model, or simply attempting to learn more from your business practices or customer behaviors, you might need a more hands-on approach to data science. And if you’re not sure where to turn for your data science needs, you might need a data science partner that can help diagnose your data needs before helping to satisfy them.

    Understanding your data science needs will help you identify the right team members for the job.

    How do I form the right data science team?

    Let's talk about how to form a data science workforce that improves your organization’s use of the information you collect.

    When determining which type of data science team you’re assembling, there are a few important steps to keep in mind.

    1. Identify your data science needs


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