Category Archives: Data

Cash Forecasting Models & Treasury Management

cash forecasting models methods 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 …

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Posted in AI, Data, Data analytics, Data Science, Machine Learning. Tagged with , , .

How to become a Data Analyst? Skills & Experience

data analyst skills experience jobs salaries

Do you want to become a data analyst? It’s a great career choice! Data analysts are in high demand, and with the right skills, you can make a good living doing something you love. In this blog post, we will discuss the skills required for data analysis, and provide some tips on how to acquire them. We will also recommend some courses and books that can help you get started on your data analyst career path! What is data analysis and what do data analysts do? Data analysis is the process of inspecting, cleansing, transforming, and creating data visualizations with the goal of discovering useful information, suggesting conclusions, and supporting …

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Posted in Big Data, Career Planning, Data, Data analytics, data engineering, Data Mining. Tagged with , .

Data Analyst vs Data Scientist vs Data Engineer

data analysts vs data scientists vs data engineers

There is a lot of confusion surrounding the job designations or titles such as “data analyst,” “data scientist,” and “data engineer“. What do these job titles mean, and what are the differences between them? In this blog post, we will define each title and discuss the key distinctions between them. By the end of this post, you will have a better understanding of which title is right for you! What is a data analyst? Data analysts are those who are responsible for collecting, organizing, and analyzing data. They use their findings to help businesses make better decisions. Data analysts are part of data management / governance teams. The following represents …

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Posted in Data, Data analytics, data engineering, Data Science.

What is Data-Driven Decision-Making? Why & How?

data driven decision making what why how

Data-driven decision-making is a data-driven approach to making decisions including business decisions. This data can come from data analysis, data visualization, or other data resources. Data-driven decision-makers use data in their decision process and they make decisions based on the actionable insights generated from the data. The goal is to make informed decisions while ensuring transparency across the stakeholders. In this blog post, we will discuss what data-driven decision-making is, how it differs from other types of decision-making, and why you should consider going for this method in your business! Before we dive in and understand what is data-driven decision-making, lets understand what are first principles of decision-making? What are …

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Posted in Data, Data analytics, Machine Learning. Tagged with .

What is Data Quality Management? Concepts & Examples

what is data quality and why is it important

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 …

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Posted in Data, Data analytics. Tagged with , .

Data Governance Framework Template / Example

data governance framework template

Data governance is a framework that provides data management governance. It’s the process of structuring data so it can be governed, managed and used more effectively. Data governance framework forms the key aspect of data analytics strategy. This blog post will discuss key functions of a standard data governance framework and can be taken as a template or example to help you get started with setting up your data governance program. What is Data Governance Framework? The data governance framework is intended to put some structure around how data can be managed and used in an organization based on well-defined rules and processes around a variety of data related operations and decisions. Data …

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Posted in Data, Data analytics. Tagged with , .

How to Create Data-Driven Culture: Key Steps

how to create data-driven culture

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 …

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Posted in Data, Data analytics. Tagged with .

Data Readiness Levels Assessment: Concepts

data readiness levels assessment

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 …

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Posted in Data, Data analytics, Data Science. Tagged with , .