XOps: The right approach for production business applications

XOps: The right approach for production business applications

Contemporary business applications face challenges on multiple fronts. A XOps approach will help organizations stay ahead. Contemporary organizations rely on business applications to help make critical decisions. Data about the business, competitors, the environment, and more are visualized in multiple ways.

An Expert Guide on AI Consulting

An Expert Guide on AI Consulting

The propensity for enterprises to adopt AI has been at an all-time high for the last decade. From automating tasks to predicting possible pitfalls and improving efficiency, AI has a plethora of use cases in the business sector today.

Artificial Intelligence In Healthcare: Benefits and Applications

Artificial Intelligence In Healthcare: Benefits and Applications

The ongoing COVID-19 pandemic overwhelmed the healthcare sector and exposed its limitations. But, it also opened the aperture for the adoption and scaling of artificial intelligence (AI) to solve critical healthcare challenges and make many aspects of healthcare more efficient.

Scaling Trade Promotion Effectiveness using Kubeflow

Scaling Trade Promotion Effectiveness using Kubeflow

When deploying ML projects, the Kubernetes-powered Kubeflow ecosystem has a good shot at tackling scaling and infrastructure dependencies. It is the best fit for Trade Promo Effectiveness (TPE) models, which run at scale with incremental data loads.

Data Drift Detection in Time Series Forecasting

Data Drift Detection in Time Series Forecasting

Changes in the data distribution are monitored with Data Drift, one of the most common indicators when monitoring MLOps models. It is a metric that measures the change in distribution between two data sets.

NLP Anthology (Part 4) – Multi-label Document Tagging

NLP Anthology (Part 4) – Multi-label Document Tagging

This blog is the last in the 4-blog series that explores the multi-label document tagging method. The specific problem statement is to label these transcript documents into client-defined categories, which will be further used in automatic routing, identification of category overlaps, etc.

NLP Anthology (Part 3) – Natural Language Intent Recognition

NLP Anthology (Part 3) – Natural Language Intent Recognition

In the modern business landscape, timing is everything. Quickly identifying user’s intent can help you get a leg up your competition. How? It can enable you to respond actively to a potential customer’s interest and multiply your chances of influencing the key decision-makers through meaningful conversations.

NLP Anthology (Part 2) – Key Concept Extraction

NLP Anthology (Part 2) – Key Concept Extraction

The COVID‐19 pandemic that hit us last year brought a massive cultural shift, causing millions of people across the world to switch to remote work environments overnight and use various collaboration tools and business applications to overcome communication barriers.

NLP Anthology (Part 1) – Intelligent Audio Transcript Analytics

NLP Anthology (Part 1) – Intelligent Audio Transcript Analytics

Machine learning – a tech buzz phrase that has been at the forefront of the tech industry for years. It is almost everywhere, from weather forecasts to the news feed on your social media platform of choice. It focuses on developing computer programs that can acquire data and “learn” by recognizing patterns and making decisions with them.

Critical MLOps Roadblocks that Will Slow Your Enterprise AI Journey

Critical MLOps Roadblocks that Will Slow Your Enterprise AI Journey

Machine learning – a tech buzz phrase that has been at the forefront of the tech industry for years. It is almost everywhere, from weather forecasts to the news feed on your social media platform of choice. It focuses on developing computer programs that can acquire data and “learn” by recognizing patterns and making decisions with them.

MLOps: Only Way to Eat the Elephant?

MLOps: Only Way to Eat the Elephant?

The blog elucidates how MLOps provides the means to build & deploy successful ML models to make the retail/CPG/BFSI/healthcare industries agile.

Predicting Order Cancellations: How ML-solution Saved Thousands of Drivers’ Hours

Predicting Order Cancellations: How ML-solution Saved Thousands of Drivers’ Hours

‘Efficiency’ roots from processes, solutions, and people. It is one of the main driving forces leading to significant changes in the way companies work in the first decade of the 21st century. The following decennary further accelerated this dynamic. Now, post-COVID, it is vital for us to become efficient, productive, and environmentally friendly.

What generally gets ignored in the B2B dynamic pricing solution?

What generally gets ignored in the B2B dynamic pricing solution?

Nowadays, corporate executives recognize that analytics is pivotal for pricing teams to create solutions that enable them to achieve their firm’s pricing objectives. In the B2B domain, ‘dynamic pricing’ is a critical approach to bring substantial benefits to companies.

First look at Performance Improvements in Spark 3.0 on Databricks

First look at Performance Improvements in Spark 3.0 on Databricks

On June 18, 2020, Databricks announced the support of Apache Spark 3.0.0 release as part of the new Databricks Runtime 7.0. Interestingly, this year marks Apache Spark’s 10th anniversary as an open-source project. The continued adoption for data processing and ML makes Spark an essential component of any mature data and analytics platform.

MLOPs Series – Part 1

MLOPs Series – Part 1

Machine learning – a tech buzz phrase that has been at the forefront of the tech industry for years. It is almost everywhere, from weather forecasts to the news feed on your social media platform of choice. It focuses on developing computer programs that can acquire data and “learn” by recognizing patterns and making decisions with them.

CI / CD / CM with ML Works

CI / CD / CM with ML Works

Most of us are familiar with Continuous Integration (CI) and Continuous Deployment (CD) which are core parts of MLOps/DevOps processes.  But Continuous Monitoring (CM) may be the most overlooked part of MLOps process, especially when you are dealing with machine learning models. In the first part of this series, we looked at some of the challenges in scaling and maintaining ML projects in a company.  In part 2, we are going to look at how Tredence is helping customers overcome these challenges.

COVID 19 : THE “UNPRECEDENTED” PLANNING PROBLEM

COVID 19 : THE “UNPRECEDENTED” PLANNING PROBLEM

If there is a word that has seen a spike in usage over the three months, then it must be “UNPRECEDENTED.” There is no better word to describe the situation that businesses and people are faced with today in the face of CoVID 19 pandemic. There are three clear phases in which this event has played out – 1. Pre-CoVID 2. During CoVID and 3. Post-CoVID

Re-imagining marketing strategies in the wake of COVID-19

Re-imagining marketing strategies in the wake of COVID-19

Wine, Cheese and Blue Jeans – all of them get better with age.

What about ideas? For most ideas, the opposite is true. Who remembers the revolutionary 5 ¼ floppy disk? At a certain point, ideas need to be debunked. Alternative and novel approaches are needed.

Role of AI/ML in Finance Process Automation

Role of AI/ML in Finance Process Automation

Document Reconciliation and Accounts Process automation both these terminologies go hand in hand these days. Organizations are increasingly looking to automate their reconciliation processes mainly to address the following issues:

Getting your Customer Delivery Promise Right

Getting your Customer Delivery Promise Right

Customer satisfaction has become the central point in the E-commerce industry to attract new customers and, most importantly, retain them in the long run. Companies are competing to deliver products as fast as they can in a fast-paced environment. Corporations like Walmart, Amazon, and Home Depot are launching initiatives in this direction like the same day, 1-day, and 2-day delivery promises.

ML Ops: Key to Accelerated Business Outcomes and Increased Last Mile Adoption

ML Ops: Key to Accelerated Business Outcomes and Increased Last Mile Adoption

You have just completed a machine learning pilot, tackling a challenging business problem which has stymied your executives for the last few years. As the plaudits roll in, you start thinking about how to move your project from the pilot stage to a full-blown application which will drive business value to your stakeholders…..

COVID-19 – Impact on Hospitality Industry

COVID-19 – Impact on Hospitality Industry

The COVID-19 pandemic is fast becoming one of the biggest threats to human lives and the global economy. With governments across the world taking preventive measures of quarantine, social distancing and travel bans, hospitality is one of the first industries to be adversely hit. The impact is not just limited…

Retailers in the time of Coronavirus Pandemic

Retailers in the time of Coronavirus Pandemic

The Coronavirus outbreak seems to be having an unprecedented effect globally. While brave health workers are confronting the fatal virus head on, business leaders from several service providers are playing an important role in the background. In addition to medicine and healthcare, basic food items…

Machine learning based Data Quality Management using Azure Databricks

Machine learning based Data Quality Management using Azure Databricks

Good quality data is extremely important as it directly impacts business insights and this could be in the form of structured data sources like Customer, Supplier, Product etc. or unstructured data sources like sensors and logs. Traditional rule-based methods to manage data quality is no longer efficient…

MLOps – The Rise of MLo16n (ML Operationalization)

MLOps – The Rise of MLo16n (ML Operationalization)

Let me start this post with a provocative statement: More machine learning models than ever, but are they making it into Production? Or more provocative even: once the ML models make it to production, are the IT Support teams equipped to run it, maintain it, manage it and above all safeguard the investments made on these breakaway enterprise assets?

How AI Application is set to revolutionize the CPG Industry

How AI Application is set to revolutionize the CPG Industry

The era of Artificial Intelligence (AI) has already begun, and various industries are investing heavily in creating self-evolving AI applications. The CPG industry (consumer packaged goods) is carefully taking note and slowly establishing new applications to improve efficiency and decrease expenses. Businesses on the frontline of AI application …

Transformation of Model Factory in the age of AI

Transformation of Model Factory in the age of AI

AI has become the pillar of growth for companies when it comes to maintaining relevance as well as an edge over the competition. What’s more, AI based models have become the new revenue drivers for companies looking to capitalize on data as a competitive advantage. The rise in algorithmically driven successes can be attributed primarily to enhancements…

Do I need to be a programmer for a career in Data Science?

Do I need to be a programmer for a career in Data Science?

Priya, a budding data scientist, was upset when she was bombarded with programming-related questions in her recent job interview. “I spent the last two years working on various modelling techniques, but now I am being asked questions about Python? I would like to build my career in data science and not in application development,” she said, with genuine doubts…

Defining MTO and MTS Production Strategy and its Implementation

Defining MTO and MTS Production Strategy and its Implementation

A reliable vendor management system must execute performance-oriented deliverables within a stipulated time frame without errors. High-tech makers of industrial machinery are, thus, in constant lookout for such ‘Make-To-Order’ process settings…

Product Management in the data science world

Product Management in the data science world

The topic related to ‘Product Management’ has received quite a flake in recent years. Several rounds of discussions have happened to create an analogy out of client’s stand point.
As I heard more of these conversations, there …

Bringing the promise of ML to your MDM : Part II

Bringing the promise of ML to your MDM : Part II

‘Augmented data management’ is a key trend where AI/ML is transforming how enterprises manage their data.
In the last article, we looked at some of the key pain points that exist as IT and business leaders …

The New Age of Customer Satisfaction

The New Age of Customer Satisfaction

Let us start with an oft repeated question,” What do you know about your customer’s preferences”?
The answer could be any of the standard responses which talk about their tastes in your merchandise based on past transactional records…

Applications of AI in Document Management

Applications of AI in Document Management

“We are drowning in information, but starved for knowledge”
This is a famous quote by John Naisbitt which shows the key difference between information and knowledge.

Bringing the promise of ML to your MDM: Part 1

Bringing the promise of ML to your MDM: Part 1

Enterprises are rushing to transform themselves, and embrace the promise of digital transformation; and while the means to achieve this end are disputed, there is unanimous agreement on the fact that reliable data is the starting point.