Tag Archives: data analytics

Data-Driven Decision Making: What, Why & How?

data driven decision making what why how

Data-driven decision-making is a data-driven approach to making decisions to achieve desired outcome. More precisely, data-driven decision making is an insights-driven approach to drive decisions and related actions. The data can come from internal and external data sources to avoid data biases. Data-driven decision-makers use data in their decision process to validate existing actions or take new actions (predictive or prescriptive analytics). They make decisions based on the actionable insights generated from the data. The goal is to make informed decisions while ensuring trust & transparency across the stakeholders & organization as a whole. It can be noted that data-driven decision making provides great thrust to digital transformation initiatives. In …

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

Data Analyst Technical & Soft Skills

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 these days. Companies rely on data analysts to help them make better decisions by turning data into insights. In order to be successful, data analysts need a mix of technical skills and soft skills. Technical skills include expertise in analyzing data. Soft skills include communication and problem-solving skills. Data analysts must be able to take data and turn it into insights that help their company make better decisions. They also need to be able to effectively communicate those insights to people who may not have a technical background. In this blog …

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

Digital Twins & its Types: Concepts & Examples

digital twins of aeroplane

You’ve probably heard of the term “digital twin” but aren’t sure what it means or how it can help your business. A digital twin is a virtual replica of a physical object or system. There are various different types of digital twins such as component, asset, system and process twins. Digital twins have become an important part of Industry 4.0 and the Internet of Things (IoT). They allow companies to improve product quality, optimize operations and reduce costs. For example, Airbus uses digital twins to monitor the health of its aircraft engines in real time. This helps them to identify potential problems early and take preventative action. In this blog …

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Posted in digital transformation, Digital Twin. Tagged with , .

Building Data Analytics Organization: Operating Models

Data analytics organization

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 …

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Posted in Big Data, Data, Data analytics, data engineering, Data lake, Data Science. Tagged with , , .

Differences: Data Analyst & Business Analyst

business analyst vs data 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 …

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Posted in Data, Data analytics, Product Management. Tagged with , .

What are Actionable Insights: Examples & Concepts

actionable insights concepts examples

The idea of actionable insights is something that has gone mainstream across different departments in any and every business due to the onset of digital transformation initiatives at large. Today, actionable insights are at the heart of many successful business decisions, and are used to help your company grow further than ever before. Actionable insights are key to any data analytics initiatives including decision-centric data analytics which are at the heart of digital transformation. Analytics centered around actionable insights is also termed actionable analytics. In this blog post, actionable insights are explained with examples along with few actionable analytics tools which are used when dealing with actionable insights. What are …

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Gartner Data Analytics Trends for 2022

Gartner data analytics trends 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 …

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

Purpose of Dashboard: Advantages & Disadvantages

Dashboard - advantages and disadvantages

A dashboard is a visual representation of the most important information needed to achieve a goal. Dashboards form an integral part of analytical solutions. As the demand for data analytics continues to grow, dashboards are well-positioned to become one of the most essential tools in any business toolkit. It can provide an overview of what is happening in your business and help you make better decisions. While there are many advantages to using a dashboard, there are also some disadvantages that you should be aware of. In this blog post, we will discuss the purpose of the dashboard and its advantages and disadvantages. As a product manager/business analyst and data …

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ESG Metrics & KPIs and ESG Reporting Concepts

ESG KPIs and metrics

This blog post is geared toward Environmental, Social & Governance (ESG) professionals looking to understand different aspects of ESG and some metrics that can be reported via ESG reports as part of their organization’s ESG reporting in relation to representing the sustainability aspect of their business. An understanding of different aspects of ESG can help you in getting started with ESG initiatives and ESG reporting. ESG initiatives can help companies improve their overall sustainability factor while creating a positive impact on environmental, social, and governance issues.  Getting started with ESG-related practices in your organization or department (such as procurement) requires a set of ESG initiatives and related performance measures including …

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Posted in Data analytics, Procurement. 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 , .

Digital Transformation Strategy: What, Why & How?

digital transformation what why and how

Digital transformation is a digital strategy that aims to change the way an organization operates. It’s not just about digital marketing anymore – digital transformation includes all aspects of digital engagement from customer service, product development, and delivery, operations, etc. And it requires a holistic approach to digital transformation without any silos or strategic gaps in between departments. In this blog post, we will cover what digital transformation is and why organizations should take advantage of this strategy. We’ll also look at how digital transformation is happening in different industries. What is digital transformation? Digital transformation is a digital strategy that aims to change the way an organization operates and …

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Posted in Data Science. Tagged with , .

Analytical thinking & Reasoning: Real-life Examples

analytical thinking 1

Analytical thinking and analytical reasoning are two concepts that are often misunderstood. Many people think that they are the same thing, but this is not the case. In fact, analytical thinking and analytical reasoning are two very different things. Analytical thinking is an important aspect of analytical skills. Most of us do not realize how to use analytical thinking and often end up solving the problem incorrectly or half-heartedly. As data analysts or data scientists, it would be of utmost importance to acquire this skill well. In this blog post, we will learn these concepts with the help of some real-life examples. What is analytical thinking? Analytical thinking is the …

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Difference between Data Science & Data Analytics

data science vs data analytics

What’s the difference between data science and data analytics? Many people use these terms interchangeably, but there is a big distinction between the two fields. Data science is more focused on understanding and deriving insights from data, while data analytics is more focused on using pre-determined algorithms to make decisions or take action. In this blog post, we’ll explore the differences between data science and data analytics in greater detail, with examples of each. The following are key topics in relation to the difference between data science and data analytics: Different forms / purposes Different techniques Different Skillsets Different tools Different forms: Data Science & Data analytics Data science is …

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Differences Between MLOps, ModelOps, AIOps, DataOps

MLOps vs ModelOps vs DataOps

In this blog post, we will talk about MLOps, AIOps, ModelOps and Dataops and difference between these terms. MLOps stands for Machine Learning Operations, AIOps stands for Artificial Intelligence-Operations (AI for IT operations), DataOps stands for Data operations and ModelOps stands for model operations. As data analytics stakeholders, it is important to understand the differences between MLOps, AIOps, Dataops, and ModelOps. For setting up AI/ML practice, it is important to plan to set up teams and practices around AIOps, MLOps/ModelOps and DataOps. What is MLOps? MLOps (or ML Operations) refers to the process of managing your ML workflows. It’s a subset of ModelOps that focuses on operationalizing ML models that …

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

Business Analytics Team Structure: Roles/ Responsibilities

business analytics value chain

Business analytics is a business function that has been around for years, but it’s only recently gained traction as one of the most important business functions. Organizations are now realizing how business analytics can help them increase revenue and improve business operations. But before you bring on a business analytics team, you need to determine if your company needs full-time or part-time team members or both. It might seem logical to hire full-time staff members just because they’re in demand, but this isn’t always necessary. If your business operates without any external data sets and doesn’t have complex reporting and advanced analytics needs then it may be more cost-effective to …

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Posted in Data analytics, Data Science, Machine Learning, Product Management. 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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