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Data Insights for Everyone — The Semantic Layer to the Rescue

Rocket-Powered Data Science

The BI (business intelligence) analysts need to find the right data for their visualization packages, business questions, and decision support tools — they also need the outputs from the data scientists’ models, such as forecasts, alerts, classifications, and more. Register to attend and view the webinar at [link].

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Analytics Insights and Careers at the Speed of Data

Rocket-Powered Data Science

Focus on the strategies that aim these tools, talents, and technologies on reaching business mission and goals: e.g., data strategy, analytics strategy, observability strategy ( i.e., why and where are we deploying the data-streaming sensors, and what outcomes should they achieve?).

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What’s next for digital transformation?

CIO Business Intelligence

The messages delivered from both the supply and demand sides of the tech industry back then were not terribly different from those currently pulsing through podcasts, webinars, zoom calls, and analyst whitepapers today. IT strategy in the digital age. Spend more time on strategy. Executives need to spend more time on strategy.

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Solving the Data Daze – Analytics at the Speed of Business Questions

Rocket-Powered Data Science

Beyond the early days of data collection, where data was acquired primarily to measure what had happened (descriptive) or why something is happening (diagnostic), data collection now drives predictive models (forecasting the future) and prescriptive models (optimizing for “a better future”). Source: [link]

Analytics 167
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The 2023 Supply Chain Crystal Ball: Challenges and Solutions

Speaker: Olivia Montgomery, Associate Principal Supply Chain Analyst

In this webinar, you’ll gain actionable insights from Olivia Montgomery as she walks us through Capterra’s extensive research on how businesses - notably SMBs - are addressing supply chain challenges in 2023. Forecasting techniques to manage inventory. Procurement strategies in response to network delays and bottlenecks.

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You cannot develop a high-quality customer engagement strategy without trust

CIO Business Intelligence

Customers must have the trust and willingness to share data As enterprises continue to create new digital-first products and services, forecasting customer needs, preparing for potential issues, and building resilience is vital to sustaining trust. These require customer data.

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Product Clustering Techniques in Demand Forecasting

DataRobot

Demand forecasting is a common Time Series use case in DataRobot. Using historical sales data, together with data related to product features, calendar of events, and economic indicators, we can produce forecasts of future demand. To improve the performance of such demand forecasting models, we can use several modeling techniques.