Monthly Archives: October 2022

Infographic: Shadow Data Creeps in the Silence

While creatures of the night might fade away after Halloween’s haunts on Monday, unknown or “shadow” data will remain lurking in the depths of organizations’ networks. Shadow data stores are more likely to be misconfigured, unmonitored, and violate data security policies — making them easy targets. In the infographic below, our friends over at Laminar discuss how it’s important to have the knowledge and tools to fight the fright all year long. 

AWS Celebrates 5 Years of Innovation with Amazon SageMaker

In just 5 years, tens of thousands of customers have tapped Amazon SageMaker to create millions of models, train models with billions of parameters, and generate hundreds of billions of monthly predictions. The seeds of a machine learning (ML) paradigm shift were there for decades, but with the ready availability of virtually infinite compute capacity, […]

Using Natural Language Processing to Uncover Valuable Insights in Text-based Data

In this special guest feature, Ryan Welsh, Co-founder and CEO of Kyndi, discusses how organizations are leveraging the latest natural language processing techniques to enable sophisticated natural language understanding. An approach that enables them to quickly discover the most pertinent answers hidden in various documents, every time a user is searching for answers in text-based data.

TruEra Launches First Automated Test Harness for ML Models with TruEra Diagnostics 2.0 Release

TruEra, which provides a suite of AI Quality management solutions for managing model performance, explainability, and societal impact, launched TruEra Diagnostics 2.0, a major update to its TruEra Diagnostics solution, incorporating the first-ever automated test harness for AI models that includes root cause analysis. The new systematic testing features in TruEra Diagnostics 2.0 help enterprises to get models into production faster by providing comprehensive model evaluation that promotes quality and transparency, accelerating model development and approval.

Cinchy Study Details How Dataware Eliminates Data Integration and Revolutionizes Application Development and Analytics

Cinchy, the dataware vendor that’s changing the way organizations work with data, released “The Rise of Dataware: An Integration-Minimizing Approach to Data,” a comprehensive analyst report that highlights a fundamental shift taking place in the data management sector. It focuses on a distinctive architectural approach that redefines the relationship between data and applications, and essentially eliminates the need for data integration as we know it.

How Newcomp Analytics partners with IBM to advance clients’ supply chain insights

When Newcomp Analytics started working with chocolatier Lindt Canada more than 15 years ago to support their supply chain, Lindt had no full-time IT personnel for analytics. Lindt now has a team of 10, including a business intelligence (BI) manager and BI developer analysts. Yet Newcomp continues to be an essential and trusted partner, helping the company keep up with the high volume of analytics solutions it needs to address. “Newcomp has a track record of delivering with no surprises,” says John Walter, IT Director at Lindt Canada.

Helping clients close the business analytics skills gap

What makes Newcomp so invaluable to clients like Lindt? The company’s up-to-date expertise with IBM Cognos Analytics and their close relationship with IBM are key factors. Brian Simpson, VP, Analytics & Performance Management at Newcomp Analytics says “Newcomp has been a strong partner with IBM for many years, dating back to the early days of Cognos Analytics. IBM has the best channel ecosystem in the market today… it’s like a well-oiled machine. They are the standard to which we hold all other vendors.”

“There’s a lot of demand for analytic skills in general, a lot of demand for Cognos Analytics… and organizations are all fighting for a limited number of resources,” says Brian Simpson. “As an IBM business partner, we can bring those skills in a temporary capacity to the organization, help them with the heavy lifting, and get the project completed, so they don’t have to have a roadblock of needing to recruit and train analytics professionals—they can do the project while building those skills in-house.”

Lindt has used Cognos Analytics for more than 20 years as an analytics solution for its sales and marketing functions. The application provided these teams with valuable business intelligence and trend analyses across a wide variety of variables from single SKUs to product categories, from store-by-store sales to regional trends, and temporal factors such as seasonality. These insights supported the company’s double-digit growth in Canada during that time.

Extending business analytics to supply chain management

Though a supply chain management team doesn’t directly influence sales, cost-to-serve factors such as transportation and palletization can have a significant influence on profitability when delivering hundreds of millions of dollars’ worth of chocolate.

Unfortunately, Lindt’s supply chain management team had been under-serviced. Left to their own devices, they had resorted to using legacy reporting tools such as Excel that required manual gathering, slicing and dicing of data. Consequently, this data was siloed, unshareable, hard to use, lacked quality and governance controls, and could not be used in automated processes.

Newcomp drew on their technical ability and extensive industry experience with CPG metrics, collaborating with Lindt to understand their business challenges and where to optimize. Working with Lindt’s key stakeholders on the supply chain team, they identified key priorities for migrating the team from its legacy tools to Cognos Analytics’ modern data analytics toolset. Lindt’s satisfaction using the application in its sales and marketing capacity bolstered their decision to expand it to the supply chain management while also supporting other key components of their technology stack including Microsoft SQL Server and Microsoft Server SSIS.

By incorporating new data feeds from transportation providers and warehouses and aggregating these to the master dataset, Newcomp developed a cost-to-serve dashboard in Cognos Analytics. Now Lindt could ask new questions and draw new insights: Why do we spend more shipping to certain retailers? How can we drill into the data to identify underlying factors and get a better outcome?

Advancing clients’ strategic data analytics capabilities

The solution, according to Brian Simpson, was “A huge advance in Lindt Canada’s business intelligence capabilities.” It helped Lindt’s supply chain management team reduce their reliance on Excel, and reduced time and effort. The data ingestion process improved data quality and governance; automation also improved data quality by eliminating manual merge and preparation of calculations. A consolidated view of data is now available through the enterprise data warehouse and through Cognos Analytics. Overall, the solution has increased the speed-to-insight and ability of Lindt’s supply chain team to share and visualize high-level KPIs from their own dashboards and data sets. It has also freed up the executive team’s time to focus on more strategic activities.

Next steps for Newcomp and Lindt: building a dynamic cube in Cognos Analytics and exploring how the company can use IBM Planning Analytics to improve forecasting and data-driven decisions for competitive advantage.

Newcomp has a strong partnership with IBM, maintaining its certifications and expertise to stay at the forefront of business analytics solutions. This in turn makes Newcomp a trusted client partner for companies such as Lindt Canada, consistently delivering value across a growing range of business functions.

Read the detailed case study to learn more about the work Newcomp Analytics and Lindt Canada are doing. To learn more about IBM Business Analytics, watch the replay of the Business Analytics Launch Event, where you can hear more case studies on how others have used IBM Cognos Analytics and IBM Planning Analytics to accelerate decision making.

The post How Newcomp Analytics partners with IBM to advance clients’ supply chain insights appeared first on Journey to AI Blog.

How to Effectively Leverage LLMs (Large Language Models) for B2B NLP (Natural Language Processing) Use Cases

In this contributed article, Rigvi Chevala, Evalueserve’s CTO, believes that while plenty of investment and progress into AI is causing great strides, ML and AI benefit from simpler solutions. LLMs offer the opportunity for a quick start, and many players are considering how to make them useful to their businesses. The article advises you to count your organization as one of them – understand their benefits and constraints and wisely use them.

ClearML and Genesis Cloud Announce New MLOps Partnership Delivering 100% Green Energy Compute Solution for Machine Learning

ClearML, the frictionless, unified, end-to-end MLOps platform, and Genesis Cloud, a leader in green GPU cloud computing, announced a new partnership. The agreement will make Genesis Cloud’s 100% green energy Compute Instance available as part of ClearML’s powerful MLOps platform. With computing accounting for nearly 4% of global emissions in 2021 – and with that number likely set […]

Capital One + Forrester Survey Reveals Key Challenges that Inhibit ML Deployment Across the Enterprise

Capital One’s new Forrester study, “Operationalizing Machine Learning Achieves Key Business Outcomes,” reveals the biggest challenges, concerns and opportunities data executives experience when leveraging machine learning to improve business performance. While the report finds that data management decision-makers are concerned about key operational challenges that could slow ML deployments and maturity, the data also reveals that adoption continues to rise, with 67% of leaders planning to increase their use of ML across their business within the next three years.

The Secret to Remaining Competitive in the AI/ML Landscape? Identify and Overcome Barriers to Scale

In this special guest feature, Marshall Choy, SVP of Product at SambaNova Systems, focuses on several trends that are affecting the future of AI/ML. 75% of business leader respondents say improving access to deep learning is very important for fostering competition and innovation in their industry. AI/ML specific chip architectures are essential to scaling effectively, but hardware engineers and IT leaders can no longer depend on the veracity of Moore’s Law – emphasizing why hardware efficiency is more important now than ever.