Category Archives: Data analytics

Top Healthcare Data Aggregation Companies

healthcare data aggregation services

Data aggregation is the process of collecting data from multiple sources and compiling it into a single database. This process is essential for healthcare professionals, companies and startups because it allows them to track and analyze patient data, which can be used to improve patient care. There are many companies that offer healthcare data aggregation services. However, not all of them are created equal. To help you choose the right company for your needs, we’ve compiled the following list of the top healthcare data aggregation companies. This list will be updated from time-to-time. Athenahealth: Athenahealth is a healthcare data aggregation company that provides electronic health records, practice management software, and …

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Posted in Data analytics, Data Mining, Healthcare. Tagged with , , , .

How to Identify Use Cases for AI / Machine Learning

identify ai and machine learning use cases

As artificial intelligence (AI ) and machine learning (ML) solutions and technologies continue to evolve, more and more businesses are looking for ways to incorporate them into their operations to realize a greater business impact. But with so many potential applications, it can be difficult to know where to start. In this blog post, we’ll outline some tips for identifying AI / ML use cases. We’ll also provide a few examples of how AI & machine learning can be used in business settings. So if you’re thinking about adding AI or machine learning to your toolkit, read on! This blog post will be appropriate for product managers, business analysts, data science …

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Posted in AI, Data analytics, Machine Learning, Product Management. Tagged with , , .

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 .

Ensemble Methods in Machine Learning: Examples

voting ensemble method

Machine learning models are often trained with a variety of different methods in order to create a more accurate prediction. Ensemble methods are one way to do this, and involve combining the predictions of several different models in order to get a more accurate result. When different models make predictions together, it can help create a more accurate result. Data scientists should care about this because it can help them create models that are more accurate. In this article, we will look at some of the common ensemble methods used in machine learning. Data scientists should care about this because it can help them create models that are more accurate. …

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Posted in Data analytics, Data Science, 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 , .

Data Lake: Design principles & Best practices

data lake concepts

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 …

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

Who is a Data Scientist? Test your Knowledge

Interview questions

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 …

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Posted in Career Planning, Data, Data analytics, Data Science, Interview questions, Machine Learning. 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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To Become a Data Analyst, Data Scientist or 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? Before selecting one of these career path, it will be good to get a good understanding about these job titles or designations, related roles & responsibilities and career potential. In this blog post, we will describe each title / designation and discuss the key distinctions between them. By the end of this post, you will have a better understanding of which career path and related designations are right for you! Shall I become a data analyst? …

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

Data-centric vs Model-centric AI: Concepts, Examples

Data centric vs model-centric AI

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 …

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

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 .

Tail Spend Management & Spend Analytics

Tail spend analysis and analytics and machine learning

Do you know where your business is spending its money? And more importantly, do you know where your business SHOULD be spending its money? Many businesses don’t have a good handle on their tail spend – the money that’s spent on things that are not essential to the core operations of the company. Tail spend can be difficult to track and manage, but with the help of spend analytics tools and machine learning, it’s becoming easier than ever before. In this blog post, we’ll discuss what tail spend is, how to track it, and how to use analytics and machine learning to make better decisions about where to allocate your …

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

OKRs vs KPIs vs VGIs: Differences and Examples

VGI vs OKR vs KPI

The difference between OKRs , KPIs and VGIs is not always clear, but the concept is a great way to measure the progress towards achieving your business objectives. As business analysts, product managers, project or team leaders, it is important to understand the concepts of OKRs, VGIs & KPIs, and what’s the difference between OKR, VGIs and KPIs. In this blog post, we will discuss OKR vs VGI vs KPI and how they can be used for setting goals / objectives and measure different aspects of your team’s and organization’s performance in relation to achieving those goals. We’ll also go over real-world examples for OKRs, VGIs and KPIs so you can …

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

Healthcare & Machine Learning Use Cases / Projects

List of machine learning topics for learning

AI & Machine learning is being used more and more in the healthcare industry. This is because it has the potential to improve patient outcomes, make healthcare more cost-effective, and help with other important tasks. In this blog post, we will discuss some of the healthcare & AI / machine learning use cases that are currently being implemented. We will also talk about the benefits of using machine learning in healthcare settings. Stay tuned for an exciting look at the future of healthcare! What are top healthcare challenges & related AI / machine learning use cases? Before getting into understand how machine learning / AI can be of help in …

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