In recent years, companies have started collecting data in all sorts of domains. This includes, for example, sales data, detail on customer behavior, or sensor data from machines and other assets. Data science is a set of tools, ideas and techniques which can be used to turn this raw data into useful insights. This knowledge can then be used in the decision-making process of the company, adding value and efficiency.
Anticipating the future by finding patterns in historical data or making your marketing more effective by grouping together customers that are similar are just some examples of how you can leverage data science in your organization. Turn your data into a competitive advantage!
Want to know more about what data science is? Read our blog to get a quick introduction to Data Science.
Why is the use of predictive analytics important for your organization?
Do you remember Blockbuster? That’s why.
Do you want to be the next (bankrupt) Blockbuster, or the next (successful) Netflix? Blockbuster went bankrupt because it didn’t adapt to the changing world around them. Netflix did, which paved the way for its digital transformation. By 2007 they had started their digital streaming platform ensuring market dominance today!
There are many ways you can leverage predictive analytics in your day-to-day. One example is increasing your forecast accuracy by using advanced models or enhancing existing ones with additional features. Could we link our demand forecast algorithms with the planned marketing spend? We could use this for more efficient stock planning. Another example could be predictive maintenance, where we predict the optimal point in time to replace an expensive (part of a) machine. This will increase the up-time of machines, and decrease repair-related downtime thereby lowering total costs. Read here how we helped the Dutch soccer club ADO Den Haag by creating a predictive model for churn using machine learning.
We at Rockfeather understand that there is no one-size-fits-all solution. That is why we tailor our solutions to the specific needs of our customers. Of course, we can also help you find out where you’re organization can leverage Data Science. That is why we offer a free-of-charge Data Science Discovery Session. After that, we can create a plan with you where the most value is and how Rockfeather can help. This can also be done by using one of our proven expertises. You can read more about our expertise on the following pages:
Moreover, we empower our stakeholders at our client’s organization, to help them anticipate changes within and outside the organization, and to be proactive in decision-making. This is how we strive to avoid disastrous situations such as Blockbuster. Our common story, between our customers and us, doesn’t end with project delivery. We train our customers to continue their business practices with our models and solutions.
At Rockfeather we stay up to date with the data analytics software landscape and keep discovering and mastering new solutions to deploy at our clients.
Are you interested in what data science can do for your organization? We would love to talk about it in a free Discovery Session.
Predictive Maintenance involves using data to track machinery health status and predict when maintenance should be performed. Effective use of predictive maintenance can prevent breakdowns and unplanned downtime and the associated costs.
Azure Machine Learning can be applied for any type of machine learning, from standard ml to deep learning, supervised, and unsupervised learning. Moreover, whether you prefer to write Python or R code or zero-code/low-code options such as the designer, you can create, shape, and track highly accurate machine learning and deep-learning models.
Changing business through data science and analytics, Alteryx lets everyone in an organization feel the thrill of getting to the answer faster. The new, end-to-end analytics platform empowers analysts and data scientists alike to create, share, and prep data, perform analysis – statistical, predictive, prescriptive, and spatial – and deploy and run analytic models.
This language is open-source, interpreted, and high-level language that provides an excellent approach for object-oriented programming. It is one of the best tools used by data scientists for various data science projects/applications. It provides great functionalities to deal with mathematics, statistics, and scientific functions.