Power BI Aggregations

Power BI was originally released as a fully cloud-based, end-user targeted data visualization tool. Now it’s both a robust and scalable enterprise-level BI ecosystem. Microsoft has increased its ability to deal with a large volume of data both imported into and hosted outside the service to implement semantic models. In this session, Wintellect Data Architect…

Making Sense of the Power BI Ecosystem

Power BI adoption growth has been astonishing. And with growing demand, we also have growing needs. The service started as an end-user-driven data visualization tool but is now at the enterprise-grade semantic layer. In this session, you will learn more about the major Power BI features and in which use cases to apply them. What…

Visualizing Data with Power BI

In this webinar, we’ll introduce Power BI to give you a lightning fast look into your data with more insight than you could ever have imagined.

An Overview of Azure Databricks

With the announcement of the general availability of Azure Databricks, in this post we’ll take this opportunity to get a brief feel to what Azure Databricks is and what it can do. What is Databricks? Databricks is a data solution that sits on top of Apache Spark to help accelerate a business’ data analytics side…

Building Language Intelligent Apps with Microsoft’s LUIS

To aid in building applications that have better natural language understanding, Microsoft came out with LUIS or Language Understanding Intelligent Services. LUIS can be used for understanding speech for the Bot Framework, Bing Speech, or even with Cortana. In this post, we’ll learn how to create a LUIS app, apply basic LUIS concepts, and how…

Developing a Routine for Performing Data Analysis with Pandas Webinar

Although there is no universally accepted approach to beginning a data analysis effort, it is typically a good idea to develop a formal process for yourself when first examining a dataset. This routine can manifest itself as a dynamic checklist of tasks that evolves as your data exploration skills progress. Exploratory Data Analysis (EDA) is…

Beginning Statistics for Data Science: Analyzing Data

In our last post we discussed different types your data can have. Now let’s focus on how to analyze on those types of data. Python code will be used to demonstrate a few of these concepts. To get things start in regards to the Python code, let’s go ahead and import our packages and review…

Getting Quick Insights on Sales Data with PowerBI

To finish off getting insights from a sales data set, we’re going to look at using Microsoft’s PowerBI. PowerBI is a very helpful tool for looking at our data through visualizations. The insights will be the same that we got in our visualization post from before, but using PowerBI we get these visualizations quicker and…

Data Analysis in Python with Pandas Webinar

Data Science, Machine Learning, and AI are all trends dominating modern computing and revolve around one important thing – data. All that data needs, is to be cleaned, and transformed in specific ways, to take full advantage of the algorithms available. During this webinar, we’ll cover Pandas, one of the best libraries in Python to…

Beginning Statistics for Data Science: Types of Data

Statistics is becoming a must learn topic for anyone looking to get into data science. Look at any data scientist job posting, and you will be hard-pressed to find a listing that does not mention a degree in statistics, mathematics, or some experience in analytics as a minimum qualification. Courses in data science are including…

Data Analysis in Python with Pandas

During this webinar, we’ll cover Pandas, one of the best libraries in Python to clean, transform, and run a quick analysis on your data. We’ll also have a look at NumPy, a library that Pandas rely so heavily upon.

Data Science for Developers

What exactly is data science?  How does one become a Data Scientist? In this webinar, you will learn how software engineers can prepare for the new age of data. The presentation will be followed by a Q&A session with Frank La Vigne. The following are some useful links about Data Science: http://playground.tensorflow.org www.franksworld.com www.datadriven.tv https://www.youtube.com/channel/UCWN3xxRkmTPmbKwht9FuE5A