IBM Big Data Hub
JUNE 26, 2018
In this Q&A, IBM financial services solution architect Irina Saburova discusses an insurance use case with IBM Data Science Marketing Lead Rosie Pongracz. In this scenario common to the insurance industry, an organization needs to adjust its operations based on upcoming weather event and multiple weather indicators can improve forecast accuracy.
DMBS2
JUNE 25, 2018
The United States has new legal limits on electronic surveillance, both in one specific way and — more important — in prevailing judicial theory. This falls far short of the protections we ultimately need, but it’s a welcome development even so. The recent Supreme Court case Carpenter v. United States is a big deal. Let me start by saying: Most fundamentally, the Carpenter decision was based on and implicitly reaffirms the Katz test.* This is good.
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Paris Technologies
JUNE 26, 2018
The budgeting and forecasting process for most organizations is long and tedious and occurs on an annual basis, at least. Companies try to do it more often to improve accuracy and aim to ultimately implement a procedure for continuous planning or rolling forecasts. Unlike any other business process, budgeting and forecasting is unique because it is […].
Mark Raskino
JUNE 29, 2018
Here’s something that I sometimes hear CEOs and other business leaders say – and seemingly without much forethought. “Of course, the technology is the easy bit.” It’s one of those trite phrases that gets picked up and repeated in everyday corporate life, as if they were statements of obvious truth and wisdom, upon which we all agree.
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Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.
IBM Big Data Hub
JUNE 27, 2018
More than 75% of C-level executives consider it a top priority to better leverage data and analytics in their decision-making. Unfortunately, less than half of individual workers say the same — a disconnect that highlights how hard it can be to make those C-level priorities a reality.
John Wheeler
JUNE 29, 2018
Have you ever been driving your car down the road when you notice the ride is bumpier than usual? Or perhaps, the car strangely veers to the right or the left? These signs point to the fact that your wheels are not balanced and aligned properly. The same can occur for integrated risk management (IRM) technology customers. Top IRM technology solutions deliver two success factors – balance and alignment – to customers seeking to add value to the business.
Data Leaders Brief brings together the best content for data, strategy, and BI professionals from the widest variety of industry thought leaders.
Jedox
JUNE 26, 2018
This is the third in a series of blogs discussing the requirements of a successful Corporate Performance Management (CPM) implementation. The first two blogs stressed the importance of Executive Involvement and explained why the Office of the CFO, not IT, should lead the implementation. This installment encourages the customer to seek a partner focused on CPM, not a vendor dedicated to selling software.
IBM Big Data Hub
JUNE 25, 2018
IBM Data Science Experience was designed to kick-start and rapidly scale data science projects, fitting any deployment needs in a multicloud environment.
Smarten
JUNE 28, 2018
This article discusses the analytical method of Hierarchical Clustering and how it can be used within an organization for analytical purposes. What is Hierarchical Clustering? Hierarchical Clustering is a process by which objects are classified into a number of groups so that they are as much dissimilar as possible from one group to another group and as much similar as possible within each group.
Hurwitz & Associates
JUNE 28, 2018
By Jean S. Bozman. Chief Data Officers (CDOs) have a weighty responsibility: they are “on point” to find the actionable insights and data trends from analysis of data lakes, data repositories and virtual “seas” of data flowing across their large organizations. Data silos, different data formats – and organizational changes combining disparate data systems – make the CDO’s tasks challenging.
Speaker: Scott Sehlhorst
We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.
CIO Business Intelligence
JUNE 25, 2018
For far too many organizations, business intelligence (BI) brings to mind simple statistical summaries in stodgy, dated reports. But beneath BI’s dull surface, keen insights await — especially for those willing to revamp their business intelligence strategy to tackle the kinds of issues forward-thinking organizations are already addressing with modern BI.
DataRobot Blog
JUNE 25, 2018
by Jen Underwood. In light of recent S-1 confessions and warnings about DOMO’s precarious situation, my condolences go out to DOMO’s customers, staff and investors. If DOMO does not pull off a successful IPO, Read More.
Smarten
JUNE 29, 2018
This article explains the Karl Pearson Correlation method of analysis, and how it can be applied in business. What is the Karl Pearson Correlation Analytical Technique? Correlation is a statistical measure that indicates the extent to which two variables fluctuate together. A positive correlation indicates the extent to which those variables increase or decrease in parallel.
Smarten
JUNE 29, 2018
This article looks at the ARIMAX Forecasting method of analysis and how it can be used for business analysis. What is ARIMAX Forecasting? An Autoregressive Integrated Moving Average with Explanatory Variable (ARIMAX) model can be viewed as a multiple regression model with one or more autoregressive (AR) terms and/or one or more moving average (MA) terms.
Speaker: Timothy Chan, PhD., Head of Data Science
Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.
Smarten
JUNE 29, 2018
This article describes the Simple Linear Regression method of analysis. What is Simple Linear Regression? Simple Linear Regression is a statistical technique that attempts to explore the relationship between one independent variable (X) and one dependent variable (Y). This method helps a business to identify the relationship between X and Y and the nature and direction of that relationship.
Smarten
JUNE 29, 2018
This article discusses the Paired Sample T Test method of hypothesis testing and analysis. What is the Paired Sample T Test? The Paired Sample T Test is used to determine whether the mean of a dependent variable e.g., weight, anxiety level, salary, reaction time, etc., is the same in two related groups. For example, one might consider two groups of participants that are measured at two different “time points” or two groups that are subjected to two different “conditions”
Smarten
JUNE 29, 2018
In this article, we will discuss the Binary Logistic Regression Classification method of analysis, and how it can be used in business. What is Binary Logistic Regression Classification? Logistic regression measures the relationship between the categorical target variable and one or more independent variables. It is useful for situations in which the outcome for a target variable can have only two possible types (in other words, it is binary).
Smarten
JUNE 29, 2018
This article describes the Spearman’s Rank Correlation and how it is used for enterprise analysis. What is Spearman’s Rank Correlation? Correlation is a statistical measure that indicates the extent to which two variables fluctuate together A positive correlation indicates the extent to which those variables increase or decrease in parallel.
Speaker: Kevin Kai Wong, President of Emergent Energy Solutions
In today's industrial landscape, the pursuit of sustainable energy optimization and decarbonization has become paramount. Manufacturing corporations across the U.S. are facing the urgent need to align with decarbonization goals while enhancing efficiency and productivity. Unfortunately, the lack of comprehensive energy data poses a significant challenge for manufacturing managers striving to meet their targets.
Smarten
JUNE 29, 2018
This article discusses the analytical technique known as Sampling and provides a brief explanation of two types of sampling analysis, and how each of these methods is applied. What is Sampling Analysis? Sampling is the technique of selecting a representative part of a population for the purpose of determining the characteristics of the whole population.
Smarten
JUNE 29, 2018
This article focuses on the Independent Samples T Test technique of Hypothesis testing. What is the Independent Samples T Test Method of Hypothesis Testing? The independent sample t-test is a statistical method of hypothesis testing that determines whether there is a statistically significant difference between the means of two independent samples. For example, one might use this method of analysis to determine whether the average value of a sedan type of car is significantly different from an S
Smarten
JUNE 29, 2018
This article describes the analytical technique of multiple linear regression. What is Multiple Linear Regression Analysis? Multiple Linear Regression is a statistical technique that is designed to explore the relationship between two or more variables (X, and Y). It is useful in identifying important factors (X,) that will impact a dependent variable (Y), and the nature of the relationship between each of the factors and the dependent variable.
Smarten
JUNE 29, 2018
In this article, we will discuss the KNN Classification method of analysis. What is the KNN Classification Algorithm? The KNN (K Nearest Neighbors) algorithm analyzes all available data points and classifies this data, then classifies new cases based on these established categories. It is useful for recognizing patterns and for estimating. Let’s say we want to determine the likelihood of loan default based on two predictors (age and loan type), with ‘default’ being the target.
Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage
Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.
Smarten
JUNE 29, 2018
This article will focus on the Naïve Bayes Classification method of analysis. What is Naïve Bayes Classification? Naive Bayes is a classification algorithm that is suitable for binary and multiclass classification. It is a supervised classification technique used to classify future objects by assigning class labels to instances/records using conditional probability.
Smarten
JUNE 27, 2018
In this article, we will discuss the Decision Tree analysis method. What is Decision Tree Analysis? There are two basic types of decision tree analysis: Classification and Regression. 1) Classification Trees are used when the target variable is categorical and, as the name implies, are used to classify/divide the data into these predefined categories of a target variable.
Smarten
JUNE 27, 2018
This article presents a brief explanation of Outliers, and how this type of analysis is used. What is Outlier Analysis? An outlier is an element of a data set that distinctly stands out from the rest of the data. In other words, outliers are those data points that lie outside the overall pattern of distribution as shown in figure below. The easiest way to detect outliers is to create a graph.
Smarten
JUNE 27, 2018
This article provides a brief explanation of the SVM Classification method of analytics. What is SVM Classification Analysis? SVM Classifications are based on the idea of finding a hyper plane that best divides a dataset into predefined classes, as shown in the image below. The goal is to choose a hyperplane with the greatest possible margin between the hyper-plane and any point within the training set, giving a greater chance of new data being classified correctly.
Speaker: David Bard, Principal at VP Product Coaching
In the fast-paced world of digital innovation, success is often accompanied by a multitude of challenges - like the pitfalls lurking at every turn, threatening to derail the most promising projects. But fret not, this webinar is your key to effective product development! Join us for an enlightening session to empower you to lead your team to greater heights.
Smarten
JUNE 26, 2018
This article provides a brief definition of the multinomial-logistic regression classification algorithm and its uses and benefits. What is the Multinomial-Logistic Regression Classification Algorithm? Logistic regression measures the relationship between the categorical target variable and one or more independent variables It deals with situations in which the outcome for a target variable can have two or more possible types.
Smarten
JUNE 26, 2018
This article provides a brief explanation of the ARIMA method of analytical forecasting. What is ARIMA Forecasting? Autoregressive Integrated Moving Average (ARIMA) predicts future values of a time series using a linear combination of its past values and a series of errors. This analytical forecasting method is suitable for instances when data is stationary/non stationary and is univariate, with any type of data pattern, i.e., level/trend/seasonality/cyclicity.
Smarten
JUNE 26, 2018
This article describes chi square test of association and hypothesis testing. What is the Chi Square Test of Association Method of Hypothesis Testing? It is used to determine whether there is a statistically significant association between the two categorical variables. This technique is used to determine if the relationship exists between any two business parameters that are of categorical data type.
Smarten
JUNE 25, 2018
This article provides a brief explanation of the KMeans Clustering algorithm. What is the KMeans Clustering algorithm? The KMeans Clustering algorithm is a process by which objects are classified into number of groups so that they are as much dissimilar as possible from one group to another, and as much similar as possible within each group. KMeans Clustering is a grouping of similar things or data.
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