From detecting anomalies to understanding what are the key elements in a network, or highlighting communities, graph analytics reveal information that would otherwise remain hidden in your data. We will see how to integrate your graph analytics with Linkurious Enterprise to detect and investigate insights in your connected data.

What is graph analytics

Definition and…

Predictive analytics uses current and historical data in order to determine the probability of a particular outcome. This is a particularly powerful approach when it is applied to medical diagnosis. In an effort to reduce misdiagnosis, historical data of former patient’s symptoms may be applied to the assessment of a new patient.

While doctors are the ultimate experts and decision-makers, using predictive analytics as a means of establishing precedent for…

There is no need to get confused with multiple linear regression, generalized linear model or general linear methods. The general linear model or multivariate regression model is a statistical linear model and is written as Y = XB + U.

Usually, a linear model includes a number of different statistical models such as ANOVA, ANCOVA, MANOVA, MANCOVA, ordinary linear regression, t-test and F-test. The GLM is a generalization of multiple…

Companies and enterprises are facing a daily grind, while they are also required to see to it that their customers are happy & satisfied, operations is efficient and employees are satisfied; and all this makes running the business – a real challenge. “Audience is the new business model”, and if any organization is struggling miserably to communicate with customers or their audience, there certainly is a negative impact of it across the business plan,…

Businesses across the globe are facing the brunt, one of huge data influx and second of increasing data complexity and of course the market volatility. To address these challenges, companies and all their verticals are turning to data-driven analytics and insights as a means to better understand their organization’s customer bases and to grow their businesses; and manage the increasing uncertainty up to a certain extent. 

The shift from conventional…

It has been a practice followed religiously by companies and organizations to analyze how they have performed over a period of time. It is mandatory for them to do so; just that some do it to survive and some do it to thrive in concurrent…

Depending on the business objectives, social media analytics can take four different forms, namely, descriptive analytics, diagnostic analytics, predictive analytics, and prescriptive analytics.

Social media data is the new gold and analytics is its digging tool. Social Media Analytics (SMA) is the art and science of extracting valuable hidden business insights from social media media data (Khan, 2015) . SMA turns the…

Traditional computer systems and software applications don’t have what it takes to support big data. If you want to collect, store, refine, or analyze big data, you have to have the right tools. Check out the following ten tools that are specifically designed with big data in mind.

 1.    Hadoop

If you know, or are willing to…

One of my favorite things over the year was starting a personal blog. (You can find my website here if you are curious.) How did it happen? Well, I was reading an article and one quote in particular really struck me: "it's not what you know it's who you know". 

That quote really resonates with me. Throughout my life I’ve learned a lot, and…

"Information is the oil of the 21st century, and analytics is the combustion engine" Peter Sondergaard, SVP, Gartner Research

In analytics, we retrieve information from various data sources; it can be structured or unstructured. The biggest challenge here is to retrieve information from unstructured data mainly texts. Here machine learning comes into the picture to overcome this challenge. Different algorithms have been designed in different platforms…

R is widely used among scientists and statisticians to perform statistical analysis while Salesforce.com is one of the leading CRM software packages used for Marketing and Salesforce automation. Salesforce.com contains vital information regarding Leads, Customers, Contacts, Opportunities and Cases. Currently this data is mainly used for operational purposes by Sales and Marketing professionals. 

 

How about using Salesforce CRM data for predictive analysis or…

Customers... What do they like? What do they use? What kind of customers used my precious new feature? There are many reasons that any business should use customer events. Ultimately everything leads to two points: customer satisfaction and revenue.

Customer Event Data

When I first started playing with Google Analytics it was beautiful. A new world was in front of me. With only a quick setup I was able to see what's going on with my users. Many…

You’re working on the MAIN MODEL. The one that leverages half the company’s assets, and on which your paycheck and that of many others depends. You’ve already run through a stepwise, forward, and backward search of the variables, their interactions, and possible curvatures. What are the most productive things to do next?

Here are a couple of ideas…

When it comes to operating a successful business, customer service is often the key. The better service that a business can provide, the more success they can find. It is no longer enough to live by the idea that the customer is always right. It has become more…

Our work at Talent Analytics, Corp., focuses on using predictive analytics to decrease employee turnover or increase employee performance. We work with our customers to define the problem to solve, and then together identify useful data inputs to include in predictive model development.

How Valuable is Employee Engagement Data in Predictive Work?

We are often asked if many years worth of employee engagement data would be meaningful in our…

If you have BI Tools and you have business users who are expected to use these BI tools, you may be frustrated! Are your users struggling to understand a complex system, or are they restricted by dashboards created by IT to satisfy their needs? Is your data integration incomplete or inaccurate. Maybe you think you need business intelligence solution training for…

Do self-serve BI tools support data governance, integral data security and organizational IT standards and policies? In some cases, the answer is 'no'. But, that shouldn't stop you from looking at self-serve BI tools. The question isn't whether the integrity of data governance can be preserved when using self-serve BI tools. The question is really, 'which vendor…

For some, simply skimming over material with words like ‘systems analysis’ or ‘business statistical data’ causes eyes to glaze over as interest and attention vaporize into thin air like a wisp of smoke. But these business buzzwords are not so nebulous in their foundations. Analytical data and use of Big…

Analysis has been with us since the dawn of human consciousness. When early man tried to understand why an animal drops when you hit it with a rock, he made the first analysis.

Analysis means nothing more than breaking down an action or event into its individual parts in order to understand it better.

Today's world is to a great extent run by computers. With it, analysis morphed into a complex and sophisticated discipline that looks at data and data streams to…

Data environments are growing exponentially. IDC reports that compound annual growth in data through 2020 will be almost 50% per year. Not only is there more data, but there are more data sources. According to Ventana Research, 70% of organizations need to integrate more than 6 disparate data sources. At the same time, the value of unlocking that data and using it to make business decisions is also increasing. For the business user, understanding this complex data and unlocking its potential…