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Leverage 

Governance First.

The most valuable firms in the world are valued primarily for their data.  Data is an important asset to price, it changes firm valuation, and it is a key consideration for an entrepreneur starting a new firm. This asset demands strategic planning to develop and leverage it to maximum potential. 

 

Many organizations have reporting that needs to be delivered without delay.  Execution is everything and those needs can be met post haste. However, activities that fall outside of a strategy can deliver outcomes that are high risk and/or high cost.  Let us begin with strategy.

Define

Governance First.

You cannot manage what you cannot measure.

You cannot measure what you cannot define. 

  1. Identify questions that need to be answered and supporting KPIs. 

  2. Identify stakeholders, data owners and stewards. Define roles and responsibilities.

  3. Build a business glossary with definitions and business rules.

  4. Generate a data catalog and model the logical structures. 

  5. Discover your sources and manage the metadata. 

  6. Identify gaps in the application architecture and plan for remediation

  7. Define mechanics of security, storage and operations

  8. Map the data lifecycle (retention, partitioning, archiving)

  9. Plan for business continuity and disaster recovery

AssetDevelopment

Mature

Governance First.

Where is your organization now and what are your future goals?  Do you currently face a gulf or chasm to cross?

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Focus

Asset Development.

Not all data is equally valuable. It's important to align data collection and analysis efforts with the organization's strategic objectives. It's easy to fall into the trap of tracking too many KPIs, which can dilute focus and lead to confusion. To prevent this, carefully select a concise set of KPIs that are truly indicative of your performance and objectives.

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By concentrating on data that directly relates to these objectives, you avoid data overload and ensure that your efforts lead to actionable insights. Emphasize quality of over quantity. 

Curate

Asset Development.

The secret of producing useful analytics, whether AI or tabular report, is hidden in plain view.   Data quality is often the single biggest challenge but overlooked in the pursuit of more exciting goals.  Is the data complete?  Accurate?  Valid?  Properly formatted? Appropriately structured? Relevant? 

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If you wait on perfection you will never produce a dashboard.  However, questionable data quality will undermine the credibility of any analytic product.  Only a constant and sustained effort will balance those concerns.

Structure

Asset Development.

With strategic focus and definition we can attend to data design and modeling.  Is the best fit a traditional Kimball-inspired data warehouse, a data lake or a lake house? 

 

It is whatever serves the business.  That structure must be driven by business need and not from the perspective of "let's see what we can make from what we have."  Business Intelligence may live in a read-only world but our role is to impose structure to answer the specific questions of the business.

Secure

Risk and Compliance

Being lax about IT infrastructure and cyber security is no small matter. State and federal governments are quickly recognizing the systemic risk posed by companies not doing what they should to keep sensitive data safe. Poor IT and security management threaten privacy and safety and those threats have only become greater over time.

We deploy best-in-class enterprise-level security products and create a bespoke security maintenance and monitoring process that fits your company and industry. Our goal is to allow you to meet any regulatory requirements you need to operate a secure, compliant business.

RiskandCompliance

Comply

Risk and Compliance

Governments are passing strict data protection and cyber security compliance laws. If a business fails to effectively meet these mandates, it risks being hit with expensive fines. More importantly, a security breach could cause millions of dollars in lost revenue, legal liability and reputation damage.  In addition to civil penalties, an improperly handled data breach can lead to criminal liability

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We help companies easily comply with the most rigorous regulatory compliance standards.  Our advanced AI tools allow our clients to stay compliant in real-time, no matter the number of different locations and their geographic dispersion. 

Explore

Visualization

Data is often complex and voluminous, making it challenging for non-technical stakeholders to derive meaningful insights. Data visualization simplifies this complexity by converting raw data into visually appealing charts, graphs, and dashboards. Data visualization often allows for interactivity, enabling clients to explore the data and drill down into specific aspects of interest. This interactive aspect fosters a culture of data exploration, enabling clients to ask questions and seek insights directly from visualizations.  It encourages a more proactive and curious approach to data analysis, leading to continuous learning and discovery. 

Communicate

Visualization

Data visualization not only simplifies the understanding of data but also facilitates persuasive and compelling communication. Visualizations can tell a story that engages your clients, helping them grasp the implications of the data. Data visualization aids in creating a shared understanding and commitment to action. Whether you're presenting findings to executives, sharing performance metrics with a team, or conveying data-driven recommendations, the visual element is often more impactful than presenting raw numbers or lengthy reports.

Decide

Visualization

Data visualization empowers your clients to make more data-driven and effective decisions. When data is presented visually, it becomes easier to understand trends, relationships, and key takeaways. This improved clarity and understanding not only save time but also empower decision-makers to make more informed choices.  This can be particularly important for strategic decisions, resource allocation, and performance optimization. In the long term, making better decisions based on well-visualized data can lead to increased efficiency and competitiveness.

AI

Classify

Artifical Intelligence 

Machine learning models can be harnessed for classification tasks by leveraging its ability to autonomously learn and recognize patterns within data. Through supervised learning, the AI model is trained on a labeled dataset, learning to associate input features with specific predefined classes or categories. The trained model can then accurately classify new, unseen data based on the patterns it has learned during training.

 

Feature Importance is also a product of classification and a critical tool to understanding which factors impact a given outcome.   When evaluating a loan portfolio, insights into what causes a charge-off can impact underwriting, marketing and product design.  Whether it's managing risk with underwriting or identifying customer preferences, AI's classification capabilities provide a powerful tool that  supports decision-making, automation of processes and changes policies. 

Predict

Artifical Intelligence 

Forecasting future events involves moving beyond classification to a time-series prediction. AI-driven predictive models can help forecast financial trends, customer behavior, and potential risks based on historical transactional data.

 

While generative AI primarily focuses on creating synthetic data, interpretative models and analytics play a crucial role in explaining the insights derived from transactional data, aiding in making informed decisions and ensuring regulatory compliance.

Explain

Artifical Intelligence 

Generative and RAG AI can be a valuable tool for explaining data insights, especially in complex and high-dimensional data sets. It provides both quantitative and qualitative explanations that help users, including data analysts and decision-makers, understand the underlying relationships and make informed decisions based on the data.

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​Generative AI can generate natural language explanations to describe the data insights it has uncovered. Ad-hoc querying of data can be done at much lower cost without the involvement of a BI analyst in each request.  Counterfactual Explanations can explain what might have happened if certain variables or conditions were different, which is of value in longer term planning and risk management.

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Perhaps where Generative AI can shine the most is consuming large and complex resources and rapidly generating applications and documentation, taking process automation to a new level.

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