Category Archives: Data
Data Lake: Design principles & Best practices
In today’s business world, data is king. The more data you have, the more insights you can glean about your customers, your products, and your operations. And the best way to collect and store all that data is in a data lake. A data lake is a data management and analytics platform that offers several benefits over traditional data warehouses. Data lakes have gained in popularity in recent years due to the growing volume of data being generated by businesses and organizations of all sizes. But before you can reap the benefits of a data lake, you need to design it correctly. The people who should be involved in designing …
100 Interview Questions for Deep Learning
If you’re looking for a job in deep learning, you’ll need to be prepared to answer some tough questions. In order to help you get started, we’ve put together a list of 100 interview questions for deep learning. While many of these questions are related to deep learning concepts, we have also listed several frameworks (Tensorflow, Pytorch, etc) related questions. By being prepared for these questions, you’ll be able to demonstrate your knowledge and expertise in this area, and increase your chances of landing the job! What is deep learning? How does machine learning differ from deep learning? What are the differences between shallow and deep learning? How does deep …
Building Data Analytics Organization: Operating Models
Most businesses these days are collecting and analyzing data to help them make better decisions. However, in order to do this effectively, they need to build a data analytics organization. This involves hiring the right people with the right skills, setting up the right infrastructure and creating the right processes. In this article, we’ll take a closer look at what it takes to set up a successful data analytics organization. We’ll start by discussing the importance of having the right team in place. Then we’ll look at some of the key infrastructure components that need to be put in place. Finally, we’ll discuss some of the key process considerations that …
Differences: Data Analyst & Business Analyst
Data analysts and business analysts are two very different positions in the world of business. Data analysts are responsible for examining data and manipulating it into a format that is easy to understand, while business analysts are responsible for taking this data and using it to make informed business decisions. This is not to say that one job is more important than the other – both positions are necessary for a well-functioning company. However, it is important to understand the distinctions between these two jobs so that you can better identify which role you might be interested in pursuing. Data Analysts vs Business Analysts Data analysts and business analysts are …
Who is a Data Scientist? Test your Knowledge
Do you know what a data scientist is? You may think you do, but take this quiz to find out for sure! Data scientists are essential to modern business and it’s important to know who they are and what they do. This quiz is just for fun, but it’s also a great opportunity to learn more about one of the most in-demand professions today. So put your data scientist knowledge to the test and see how well you really know this profession! And, feel free to share your thoughts if you disagree with the answer of any of the questions. Here are a few related posts on this topic: What …
Data-centric vs Model-centric AI: Concepts, Examples
There is a lot of discussion around AI and which approach is better: model-centric or data-centric. In this blog post, we will explore both approaches and give examples of each. We will also discuss the benefits and drawbacks of each approach. By the end of this post, you will have a better understanding of both AI approaches and be able to decide which one is right for your business! As product managers and data science architects, you should be knowledgeable about both of these AI approaches so that you can make informed decisions about the products and services you build. Model-centric approach to AI Model-centric approach to AI is about …
Gartner Data Analytics Trends for 2022
Every year, Gartner releases a report on the latest data analytics trends that will be influential for businesses in the coming year. These reports are always insightful, and provide valuable information for companies who want to stay ahead of the curve. This year is no exception, and Gartner released their predictions for data analytics trends in earlier in 2022. In this blog post, we will take a look at some of the most important trends that Gartner has identified. Although it is a bit late to publish this post. However, this post discusses the concepts in detail and will be updated from time-to-time. Stay tuned for more insights into the …
Marketing Analytics Machine Learning Use Cases
If you’re like most business owners, you’re always looking for ways to improve your marketing efforts. You may have heard about marketing analytics and machine learning, but you’re not sure how they can help you. Marketing analytics is an essential tool for modern marketers. In this blog post, we will discuss some of the ways marketing analytics and AI / machine learning / Data science can be used to improve your marketing efforts. We’ll also give some real-world examples of how these technologies are being used by businesses today. So, if you’re ready to learn more about marketing analytics and machine learning, keep reading! What is marketing and what are …
What is Human Data Science?
There’s a lot of buzz around the term “human data science.” What is it, and why should you care? Human data science is a relatively new field that combines the study of humans with the techniques of data science. By understanding human behavior and using big data techniques, unique and actionable insights can be obtained that weren’t possible before. In this blog post, we’ll discuss what human data science is and give some examples of how it’s being used today. What is human data science? Human data science is the study of humans using data science techniques. It’s a relatively new field that is growing rapidly as we learn more …
Cash Forecasting Models & Treasury Management
As a business owner, you are constantly working to ensure that your company has the cash it needs to operate. Cash forecasting is one of the most important aspects of treasury management, and it’s something that you should be paying attention to. Cash forecasting is a great example of where machine learning can have a real impact. By using historical data, we can build models that predict future cash flow for a company. This enables treasury managers to make better decisions about how to allocate resources and manage risks. As data scientists or machine learning engineers, it is important to be able to understand and explain the business value of …
What is Data Quality Management? Concepts & Examples
What is data quality? This is a question that many people ask, but it is not always easy to answer. Simply put, data quality refers to the accuracy and completeness of data. If data is not accurate, it can lead to all sorts of problems for businesses. That’s why data quality is so important – it ensures that your data is reliable and can be used for decision-making purposes. Data is at the heart of any enterprise. It is essential for making sound business decisions, understanding customers, and improving operations. However, not all data is created equal. In order to make the most out of your data, you need to …
How to Create Data-Driven Culture: Key Steps
In today’s competitive business environment, companies are looking for the cutting edge they can get to stay ahead. One of the ways to beat the competition is by establishing a culture of data-driven decision making. In this blog post, we will explore how to create a data-driven culture that values data analytics and provides actionable insights into what needs to be done next in order to create a future-ready digital organization. What is data-driven culture? Data-driven culture is about creating an organization that is data-driven, where everything from business processes to culture supports the need for data-based decision making. In other words, every step of a business process must be …
Data Readiness Levels Assessment: Concepts
Data readiness levels (DRLs) and related assessments are an important part of data analytics. Data readiness levels is a concept where different stages represent the quality and maturity of data. Data science is becoming increasingly popular, but not all companies have the right level of data readiness for this type of work. Performing data readiness levels assessment is important because it gives an insight into the quality and quantity of your current datasets and helps determine future success of the data analytics project. This blog post will explain what data readiness levels are and why assessment tests are important in relation to them. What are data readiness levels? Data readiness …
I found it very helpful. However the differences are not too understandable for me