September 2023 – 🔴 Red Button Data

Data Management LIGHTSONDATA

Sep 27 2023

5 Steps to Achieve Proactive Data Observability – Explained Over Beers

In the multifaceted realm of data management, aspiring to master proactive data observability often mirrors the meticulous craftsmanship that goes into brewing the quintessential batch of beer. It is a symphonic endeavor that calls for a harmonious blend of varied elements, a craft demanding skill, finesse, and an adept understanding of the underlying balances at […]

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Blockchain-Based LLMs: A Game Changer for Data Privacy Protection

In today’s digital age, data privacy has become a major concern for individuals and organizations alike. With the increasing number of data breaches and unauthorized access to personal information, the need for robust data privacy protection measures has never been more pressing. That’s where blockchain-based large language models (LLMs) comes into play. Blockchain is a […]

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How to Optimize Customer Analytics to Improve the Post-Purchase Customer Experience

In a recent Martechcube survey, only 18% of retail leaders believe that they could significantly improve the post-purchase customer experience. In contrast, a whopping 80% of consumers feel otherwise. Providing a poor post-purchase customer experience can prevent you from building customer loyalty. Customer analytics can provide valuable insights and data-driven strategies to help you get to know your customers, personalize customer experiences, and improve customer satisfaction.

Over-Reliance on Customer Segmentation

One of the biggest culprits underlying a poor post-purchase customer experience is segmentation. Analytics allows you to segment your customers into similar groups with similar characteristics such as income, gender, age, etc., or behaviors such as purchases, path-to-purchase, and promotional responses.

Marketers use segmentation to help them tailor their campaigns, promotions, and communication to each segment, hoping that these will resonate with customers in the same segment. But do they? Not always. People falling within a segment often have different needs, values, and motivations, and, even if they have the same behaviors, their reasons or motivations for that behavior can be very different.

Insufficient Personalization

By analyzing a customer’s purchase history, browsing behavior, demographics, and other customer activities, you can deliver targeted content, product recommendations, and offers that are more likely to resonate with the customers. More savvy retailers are bringing zero-party data into the personalization mix. Zero-party data is information from customers that they voluntarily and deliberately share with you. The use of zero-party data has risen in popularity after Google announced its intended phase-out of support for third-party tracking cookies in Chrome back in early 2020. Since this time, marketers have realized that zero-party data is more than a replacement strategy for cookie data and now understand that one of the best ways to know what a customer really wants is to simply ask the customer.

Predictive Analytics Can’t Always Forecast Churn

There’s no doubt that predictive analytics is a valuable tool that can help you predict customer behavior, such as their likelihood of churning or making a repeat purchase. Insights can assist you in proactively addressing issues and engaging at-risk customers.

On the downside, there are tons of factors that cause predictive analytics to fail to predict customer churn. Insufficient or poor-quality data will impact the accuracy of results for any type of modeling. Predictive models base their predictions on trends in historical data. As such, they might fail to predict that a customer has decided to churn abruptly due to a recent negative experience. This is a big shortfall for predictive accuracy because 76% of shoppers will stop doing business with a company after just one negative experience. In addition, the competitive landscape is constantly evolving, and historical data may not reveal this.

These shortcomings have several implications for users of predictive analytics. It’s important to regularly update predictive analytics models, validate results, and incorporate a variety of data sources, both internal and external. Also, predictive analytics needs to be part of a comprehensive data analytics approach that includes adaptive analytics strategies. For example, analyzing current data from customer support interactions, including call logs, chat transcripts, and email can quickly identify if a customer is experiencing an issue. And keeping track of new social media mentions and conversations can help you spot unhappy customers faster.

Let’s Make CX Easy Together

Customer analytics provide valuable insights to help you know your customers better to help you deliver a more engaging customer experience. But more is needed than traditional segmentation. You’re going to need to focus more on individual customers and engage with them directly to understand their needs. Advanced analytics such as predictive modeling are useful for understanding future customer behavior, but you’ll still need adaptive analytics to identify sudden changes in the customer experience or market dynamics.

According to a recent GigaOm TPC-H Benchmark Test, the Actian platform’s operational data warehouse is 9x faster and 16x cheaper than alternatives. The Actian Data Platform makes it easy to track, manage, and analyze customer analytics to better identify areas that need improvement and help improve business outcomes. Contact us to start your journey to improving CX.

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A Data-Driven Approach to Targeting Loyalists and Switchers

Today’s streaming wars continue to make headlines as the major services report subscriber wins and losses amid a period of business model reinvention. For example, while Netflix recently reported steady customer growth – including for its new ad-supported plan – Disney+ saw the loss of 4 million subscribers and Warner Bros. Discovery’s subscriber numbers fell short of analyst estimates. […]

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Five Trends Shaping Enterprise Data Labeling for LLM Development

In an era where large language models (LLMs) are redefining AI digital interactions, the criticality of accurate, high-quality, and pertinent data labeling emerges as paramount. That means data labelers and the vendors overseeing them must seamlessly blend data quality with human expertise and ethical work practices. Crafting data repositories for LLMs requires diverse and domain-specific […]

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Empowering Power BI with the Semantic Layer

Today’s organizations widely acknowledge the significance of leveraging data and analytics. Virtually every executive envisions establishing a data-driven organization. However, a survey conducted by New Vantage Partners reveals that only a mere 26.5% of companies have effectively achieved this transformative goal. Part of the problem lies in the ineffective collaboration between business and technology teams. In the […]

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The Rise and Importance of Identity Verification

Establishing and Verifying Identity in a modern and more connected world

In the expansion of our digital world, the management of identities has become a critical concern. Personally, for individuals, and more holistically for organizations in many sectors, including finance, healthcare, e-commerce, and government.

The proliferation of online services and the constant threat of cyberattacks and identity theft have underscored the importance of robust identity verification systems.

Digital Transformation and Identity Management

A more digital society has brought numerous conveniences, enabling the individual, to access services, conduct transactions, and communicate seamlessly across the globe. This digital evolution has also given rise to new challenges, primarily in the realm of identity management and verification.

The many online services have created a demand for efficient and secure identity verification systems. People now perform a myriad of activities online, from shopping and banking to social networking and e-health consultation.

As more personal information is stored online, bad actors and cybercriminals have increasingly targeted individuals’ identities for malicious purposes. Identity theft and fraud pose significant threats to both the individual and the many organizations that they potentially engage with.

Governments and regulatory bodies have recognized the importance of safeguarding personal information. Regulations like the General Data Protection Regulation (GDPR) and Know Your Customer (KYC) requirements in the financial and health sector emphasize the need for robust identity verification.

Users expect seamless and user-friendly experiences when interacting with online services and the cumbersome identity verification processes and systems of yesteryear can lead to user frustration and disengagement.

The rise of digital identity and IVS

Identity verification systems (IVS) have emerged as a vital component of modern digital ecosystems. They play a pivotal role in confirming the identity of individuals, enabling secure access to online services, and mitigating the risk of identity-related fraud.

IVS plays a crucial role in various sectors, including finance, healthcare, e-commerce, and government, to ensure that users are who they claim to be, enhance security, and comply with regulatory requirements.

For the public, organizations that rely on establishing a strong identity verification process foster increased trust between the user and the service providers. Users are more likely to engage with services they trust, leading to increased customer retention and loyalty.

Efficiency in the identity verification process also streamlines onboarding processes and reduces the need for manual verification, lowering operational costs for organizations.

Verified identities also provide improved opportunities for personalized experiences and recommendations, enhancing user engagement and satisfaction.

E-government (short for electronic government) is the use of technological communications devices, such as computers and the Internet, to provide public services to citizens and other persons in a country or region. E-government offers new opportunities for more direct and convenient citizen access to government and for government provision of services directly to citizens. Effective E-government is more easily achieved through the establishment of IVS.

His Majesty’s Revenue and Customs (HMRC) is the tax authority in the United Kingdom. HMRC uses a digital identity verification system to ensure secure access to its online services. Similarly, the US IRS (Internal Revenue Service) is the tax authority in the United States. It has implemented various digital identity verification systems to protect taxpayers’ information and prevent fraud.

Singpass is Singapore’s national digital identity system. It provides residents with a trusted digital identity for secure transactions with over 2,700 services offered by more than 800 government agencies and businesses. The Singpass National Digital Identity (NDI) scheme allows residents to seamlessly access government services and third-party apps, such as banks, colleges, professional bodies, and insurance companies.

Estonia has built one of the world’s leading e-governments with a robust digital identity verification system. Estonia’s digital public infrastructure delivers automated and reusable government services in a human-centric, secure, and private way. The country has made its building blocks open-source, available as global digital public goods for others to use. Estonia’s digital services have played a crucial role during the COVID-19 pandemic, enabling citizens to access services online without the need for physical presence

ID.me offers a US-based identity proofing and group affiliation verification that also meets the federal standards for consumer authentication. NIST 800-63-3 IAL2 and AAL2 conformant and EPCS standards, amongst others.

ID.me’s digital wallet and identity verification service simplifies how over 112M individuals discover and access benefits and services through a single login and verified identity from over 600 partners. It provides users with a trusted digital ID card to access government services and benefits. or example, you can use your verified digital ID card to manage your IRS online account, access Social Security Administration benefits and services, manage unemployment benefits and services from various state departments of labor. ID.me also offers discounts and cashback from over 5,000 stores. ID.me also provides an Rx Card that can help you save up to $95 per prescription at participating pharmacies.

ID.me’s simplicity is that it reaches out to consumers to promote the simplicity of proving their identity online, as well as helping businesses provide marketing promotions and bonuses to verified eligible users. Under the hood, it checks to see whether the customer belongs to an eligible group and triggers an invitation to the promotion. The ID.me mission statement stresses “No Identity Left Behind” promising to enable this functionality to everyone, regardless of background or banked status.

Identity Verification Approaches

The establishment and verification of identity are multifaceted processes that require careful consideration of various factors. Several approaches and technologies are employed to verify identities effectively.

In some instances the eGovernment services provide a means of identity verification that a business can leverage however these services may not be available or authorized for commercial use.

Biometrics for identity verification uses physiological characteristics to identify individuals. Biometric features may include facial recognition, fingerprints, iris or retina scans, voice recognition, hand geometry, or even behavioral traits such as typing patterns or walking gait. Such features are captured by sensors and compared with pre-existing biometric data stored in a database to confirm or deny the identity of the person. Biometric authentication systems are increasingly popular in areas such as banking, security, and mobile devices since they are considered to be more secure than traditional methods of identification, such as passwords or personal identification numbers (PINs), they are much harder to forge or steal.

Document scanning of ID documents such as passports or driver’s licenses for identity verification is a common practice in various contexts. Organizations and agencies may use ID scanning to take electronic copies of documents that prove your identity, such as driver’s licenses. ID scanning can help verify the authenticity of government-issued identifications and streamline identity verification processes.

Knowledge-Based Authentication (KBA) is an authentication method that verifies user identity by asking specific security questions. When setting up a new account, users are often required to create a password and choose security questions and answers, such as “What is your mother’s maiden name?”. During login or other actions, users are prompted to answer these security questions based on personal information. KBA can be categorized into two types: Static Knowledge-Based Authentication (SKBA) and Dynamic Knowledge-Based Authentication (DKBA).

Static Knowledge-Based Authentication requires users to provide answers to one or more security questions during account creation. The answers can be accurate or made up, as long as the user remembers them when prompted later. Enterprises need to be cautious when selecting the type and number of questions to avoid being intrusive or excessive.

Dynamic Knowledge-Based Authentication (DKBA) provides a higher level of security but is used less frequently. It relies on information collected from different data sources to generate real-time questions. For example, a user may be asked, “Which of the following companies did you not work for?” and presented with a list of former employers and one incorrect answer.

While KBA is still widely used, it has certain limitations. Personal information used for KBA can often be discovered or stolen through research, phishing, social engineering, or data breaches. People also freely share the same information on social media sites, reducing its security value. Passwords can be shared, stolen, or cracked using password-cracking tools. To enhance security, enterprises relying on KBA should reinforce it with more secure methods like MFA (Multi-Factor Authentication).

SMS or Email Codes are increasingly popular for identity verification, wherein users receive a one-time code via SMS or email, which they must enter to complete the verification process. These are extensions to older, but still popular methods like tokens; where physical devices or mobile device software generates time-based or event-based codes for authentication.

Contemporary blockchain technology offers a decentralized and tamper-resistant approach to identity verification, allowing users to control their identity data securely.

Challenges in Identity Verification

Biometric data, such as fingerprints or facial scans, is highly personal and sensitive. If not adequately protected, it can be vulnerable to data breaches or unauthorized access. Further, storing biometric data in centralized databases can create a single point of failure and increase the risk of identity theft or misuse.

Organizations must comply with local, regional, and national data protection regulations when collecting, storing, and processing biometric and other personal data. There needs to be proper consent, secure storage, and appropriate retention periods for identity and other personally identifiable information.

Biometric systems may have false acceptance or false rejection rates, leading to incorrect identification or denial of access. Factors such as changes in physical appearance, injuries, or aging can affect the accuracy of biometric matching. Denial of service or access can prove challenging under such circumstances. Compromised credentials and stolen devices present the same risks. Some of these approaches may also not work equally well for everyone. Factors such as skin color, gender, age, or disabilities can impact the accuracy and inclusivity of biometric identification systems, for example. Biases in training data or algorithms can also result in discriminatory outcomes.

Ultimately, users should have control over their biometric and other data and be able to provide informed consent for its collection and use. Organizations should be transparent about how individuals’ data is used and allow them to opt-out if desired.

IVS Market offerings

Identity verification systems have risen to prominence due to the digital transformation and the growing importance of securing personal information in the digital age. These systems provide enhanced security, regulatory compliance, improved user trust, and operational efficiencies. Various approaches, including biometric authentication, document verification, and blockchain-based solutions, are employed to establish and verify identity.

Customer Master Data Management (CMDM) primarily revolves around managing and maintaining customer data within the organization. Its core purpose is to create a unified and accurate view of customer information, ensuring consistency and reliability across various systems and departments. The Pretectum CMDM achieves this through data integration, quality management, governance practices, and consolidation efforts. Its use cases span a wide spectrum, from improving customer relationship management to enhancing data analytics and supporting marketing campaigns, sales, and customer service. Customer MDM aggregates customer data from diverse sources within your organization, amongst them, CRM, ERP. CDP, marketing and sales systems, and databases.

In contrast, IVS is tailored specifically for the critical task of verifying the identity of individuals accessing online services or systems. Its primary objective is to confirm that the person claiming to be a customer is indeed who they claim to be. IVS accomplishes this through a range of methods. IVS finds applications in online services, financial institutions, government agencies, and any organization that requires secure user authentication. Its role is to prevent fraud, secure access to sensitive data, and adhere to regulatory mandates such as Know Your Customer (KYC) requirements. IVS primarily relies on data provided by users during the verification process, including biometric data, scanned identification documents, or responses to security questions.

When comparing CMDM and IVS, several distinctions and intersections emerge. CMDM is more encompassing in scope, addressing all facets of customer data management, including data quality, integration, and governance. IVS, conversely, maintains a narrower focus on identity verification. Both CMDM and IVS contribute to regulatory compliance, with CMDM ensuring data accuracy and consistency, which is vital for adhering to data protection regulations, while IVS plays a pivotal role in identity verification and KYC compliance.

In essence, CMDM and IVS are complementary elements in the digital ecosystem. CMDM like the Pretectum Customer MDM aids in maintaining data accuracy and providing a holistic view of customer data for internal purposes within an organization, while IVS specializes in the crucial task of verifying the identity of users for the sake of security and controlled access. Both are indispensable for ensuring data accuracy, safeguarding digital interactions, and aligning with regulatory requirements. While their scopes and functions differ, they work in tandem to support trustworthy and efficient digital operations in an increasingly connected world.

Organizations must navigate the many challenges related to privacy, user experience, false positives/negatives, scalability, regulatory compliance, and continuous monitoring by appropriately selecting technologies and practices aligned with their specific operational needs.

By adopting appropriate identity verification and data management approaches, organizations can build trust with their users, enhance security, and deliver seamless digital experiences in an increasingly interconnected world. The adoption of appropriate customer master data management and identity verification systems can shape the way customers interact with organizations for their joint success and confidence in dealing with one another in the years to come.

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Sep 22 2023

CCPA vs. GDPR: Differences and Similarities for Data Protection

The California Consumer Privacy Act (CCPA) and the General Data Protection Regulation (GDPR) were created to empower individuals with greater control over their personal information. Both laws regulate the activities of organizations that collect and use data in various ways. Data protection plays an essential role in ensuring compliance with both privacy regulations. CCPA vs. […]

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What Is Metaflow? Quick Tutorial and Overview

As data science continues to evolve, new tools and technologies are being developed to help individuals and organizations streamline their workflows, improve efficiency, and drive better results. One of the most powerful and innovative tools in this space is Metaflow, a Python library that makes it easy to build and manage data science workflows. In […]

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Map Customer Journeys to Create Great Customer Experiences

Customer journey analytics interprets data from various touchpoints and interactions that a prospect or customer has with a company from end-to-end. Insights into the customer experience, behavior, and points of friction in sales and service help optimize the customer journey to improve customer satisfaction and drive better business outcomes. However, to derive these benefits you’re going to need a tool to give you a holistic understanding of customer engagement: the customer journey map.

What is a Customer Journey Map?

A customer journey map is a visual representation of stages, touchpoints, actions, and experiences that a customer goes through while engaging with a company’s products, services, or brand.

Stages of the Journey

The customer journey map reveals the stages that a customer progresses through as they engage with a company both before and after becoming a customer. Common stages include:

Awareness: The customer recognizes a need
Consideration: The customer compares options to meet the need
Decision: The customer chooses the best solution
Retention: A company’s ongoing marketing, service, sales, and communications with a customer post-purchase to promote loyalty and encourage additional purchases
Advocacy: A satisfied customer becomes a vocal supporter of the brand.

Touchpoints: Touchpoints are the interactions or points of contact that a customer has with the company, from start to finish. These can include advertising, website visits, social media interactions, customer service calls, virtual and in-person events, emails, texts, physical store visits, and more.

Customer Actions and Experiences: Alongside each touchpoint, the customer journey map highlights the actions a customer takes and customer satisfaction or dissatisfaction during each interaction.

What Insight Does a Customer Journey Map Provide?

Analyzing data from the customer journey map helps uncover patterns, trends, and correlations within the customer journey that may otherwise be overlooked. You’ll get a better understanding of how customers behave, where they engage and convert, why they might leave, and what’s next on their wish list. This data-driven approach helps you make informed decisions that optimize the customer journey.

Know Your Customers Better: By understanding customer behavior, preferences, and the factors that influence their decisions, businesses can craft more effective messages and marketing and sales campaigns.

Assess Touchpoint Effectiveness: Identifying which touchpoints are most influential in driving conversions, engagement, and customer satisfaction can lower customer acquisition costs, optimize revenue, and increase customer loyalty.

Prevent Customer Churn: With knowledge of customers who have had poor experiences, a company can identify customers who might leave and take proactive measures to retain them. The company can also take steps to ensure that customer-facing processes work better in the future.

Anticipate Future Needs: Businesses can apply predictive analytics to their customer journey data so they can anticipate what their customers might need in the future and create proactive solutions or strategies to meet those needs.

Getting Started on Your Customer Analytics Journey

The Actian Data Platform can help you get started on your customer analytics journey. It provides everything you need to unify data across customer interaction touchpoints, bringing together data from call center and website logs, social media interactions, customer relationship management, customer service applications, third-party data, and more. Using the Actian platform, you’ll have greater confidence in the data you use to inform your customer journey.

Watch our webinar for more pointers on how to build a 360-degree view of customers to provide more meaningful experiences throughout the customer journey.

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Strategies for Tackling Digital Transformation Resistance

The often-overused phrase “digital transformation” instills a sense of excitement and progress for many executives. But for some business leaders, digital transformation means intimidation or mystery. When the former group is tasked with selling data-driven technology initiatives to the latter group, they face formidable challenges. They must win hearts and minds to get buy-in, sometimes faced with […]

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Seamless Data Exchange: Best Practices for Modern Businesses

In today’s dynamic business landscape, the ability to share, receive, and process information swiftly has become a critical success factor. The rapid pace of digital transformation has amplified the demand for efficient and seamless data exchange mechanisms that allow businesses to remain agile, make informed decisions, and maintain a competitive edge. As organizations expand and […]

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How to Maximize Multi-Cloud Data Governance

The transition from hybrid to multi-cloud environments is more than just a buzzword: It’s a fundamental shift in how organizations manage and utilize their data. As these complex architectures evolve, the importance of robust multi-cloud data governance cannot be overstated. This article aims to provide an in-depth analysis, tips, and best practices for maximizing data […]

The Role of IT in Data Governance

Information technology (IT) plays a vital role in data governance by implementing and maintaining strategies to manage, protect, and responsibly utilize data. Through advanced technologies and tools, IT ensures that data is securely stored, backed up, and accessible to authorized personnel. IT also enforces data governance policies and procedures, such as data classification and access […]

Legal Issues for Data Professionals

The catapulting of data to become a new class of business assets and the rapid evolution of generative and non-generative AI requires the integration of data and law for success in today’s business environment. This new TDAN column covers this integration, and, in particular, addresses the legal issues that data professionals need to know to […]

Through the Looking Glass: Data Provenance in the Age of Generative AI

Am I right that you can’t open LinkedIn, read a tech or business blog, or attend a conference for more than 30 seconds without encountering the generative AI hype? It’s been this way ever since last fall when OpenAI unleashed ChatGPT upon a (mostly) unsuspecting world. Depending on who you read or listen to, generative […]

Use of Big Data in Investing

In a turn of events unanticipated by most analysts, young people — Gen Zers and Millennials, in particular — are outpacing older generations in 401(k) contributions. Furthermore, young people are investing earlier than ever, with 31% of Millennials having started investing before turning 21. But with growing investment opportunities for young generations and their unprecedented […]

How to Use Analytics in Web Development

It may sound a little dramatic, but in today’s ever-evolving world, data is vital. Data can be huge in boosting your business revenue and exposure. Knowing your data means being able to offer continuous improvement and optimization, which in turn will allow you to deliver even better user experiences. You can track who’s looking at your […]

When Do I Need an Object-Oriented Database Management System?

What is an Object-Oriented Database Management System?

An object-oriented database management system (OODBMS) is based on the principles of object-oriented programming. Data is created, modeled, and stored as objects, which are self-contained units that contain both data and the operations or methods that can be performed on that data.

Should your organization’s enterprise data management include an OODBMS? Here’s a quick look at where it excels and the types of applications that can benefit from these advantages.

What is an OODBMS used for?

An OODBMS is most valuable for applications with complex data relationships that require persistence, support for diverse data types, and frequent schema changes.

Complex data structures and relationships: An OODBMS is especially useful for applications with complex data structures and relationships since this type of database accommodates a more flexible and dynamic data model than relational databases. An object can store relationships that it has with other objects, including many-to-many relationships, and objects can be formed into more complex objects than traditional data models.

Performance: An OODBMS can provide improved performance compared to relational databases, especially for applications with complex data structures.

Persistence: Object databases bring permanent persistence to object storage.

Highly Extensible: Because objects can be easily modified and extended, it can be easier to evolve the data model over time.

Capable of handling diverse data types: OODBMS can store different types of data such as pictures, audio, video, text, and more.

Schema Evolution Support: The tight coupling between data and applications in an OODBMS makes schema evolution more feasible.

What are some common applications built on top of Object-Oriented Databases?

Here are some examples of applications that commonly use an OODBMS as part of enterprise data management:

Computer-aided design (CAD)/Computer-aided manufacturing (CAM): An OODBMS helps to store and manipulate complex 3D models of buildings, machine parts, etc.

Content management/digital asset management: An OODBMS handles complex schemas and structured, semi-structured, and unstructured data types, including text, images, audio, and videos.

Financial applications: An OODBMS can be useful for financial applications that need to store complex data structures such as portfolios of stocks and bonds.

E-commerce applications: An OODBMS can handle complex data such as customer orders, product catalogs, and transaction histories.

Healthcare applications: An OODBMS can provide efficient storage and retrieval of elector health records (EHRs) and medical imaging such as X-rays, MRIs, and CT scans.

Gaming applications: An OODBMS helps store and access data about game objects, such as characters and weapons, and game events such as player interactions and game state changes.

Why NoSQL?

While an OODBMS provides a more efficient way to store and access complex data structures, many of these databases lack enterprise features required for mission-critical business applications.

NoSQL from Actian is an OODBMS that doesn’t require making these tradeoffs. It provides performance, scalability, availability, and reliability. NoSQL features ACID and distributed transaction support, two-phase commit, and online schema evolution. Its two-level cache and multi-session/multi-threaded architecture are optimized for next-generation multi-core server architectures to deliver linear scalability to handle growth in data volume and concurrent user access.

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The Power of Graph Databases to Detect Fraud

Graph databases play a key role in fraud detection within intricate, complex networks, helping security teams keep pace with modern fraud techniques that are becoming increasingly more sophisticated. Graph databases can identify patterns and relationships in big data, reducing the level of complexity so that detection algorithms can effectively discover fraud attempts within a network. […]

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Data Governance in the Age of Generative AI

AI-based business models and products that use generative AI (GenAI) are proliferating across a wide range of industries. The current wave of AI is creating new ways of working, and research suggests that business leaders feel optimistic about the potential for measurable productivity and customer service improvements, as well as transformations in the way that […]

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Data Marketplace, Data Catalog, and Data Sharing Agreements: Let’s Make It Clear

As some of you already know, I am dedicating these summer days to the writing of my new book, “99 Questions About Data Management,” which follows in some way the book “20 Things You Have to Know About Data Management.” After the many questions I have received, I find it interesting to answer this one: […]

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Get Smart

Becoming progressively smarter, or continuously improving one’s intelligence and personal success, is a goal that anyone can pursue. However, naturally smart people can easily sabotage their work or social progress through certain behaviors or thoughtless acts.

If you embrace lifelong learning by reading books, taking courses, attending seminars, and staying updated with the latest information in your field you will know that this is an effective way to become progressively smarter.

Naturally smart individuals may occasionally become complacent, assuming they already know enough, which can hinder further growth. If you regularly challenge yourself with complex problems and puzzles you will find this encourages critical thinking and problem-solving skills.

Natural intelligence and over-reliance on talent can lead to relying solely on one’s innate abilities, neglecting the importance of practice and effort. Over time others will overtake you. Practices like mindfulness and meditation can improve focus, reduce stress, and enhance cognitive abilities over time.

Smart individuals may become so engrossed in their pursuits that they overlook their mental well-being, potentially leading to burnout. This can have a negative impact not only on their mental health but also on their physical health. Those who choose to focus on building a diverse social network of people with different perspectives find themselves in discussions with others on many topics which can broaden horizons and introduce new ideas and divergent thinking.

Overconfidence in one’s intelligence may lead to dismissing others’ ideas and missing out on valuable insights. Seek out feedback on your work and actively incorporate constructive criticism. This helps you identify areas for personal improvement and growth. Being naturally smart can make you sensitive to criticism, leading to you avoiding feedback or becoming defensive.

Efficient management of your time wherein you allocate enough hours for learning, work, and relaxation leads to a well-balanced schedule which can enhance personal productivity and creativity. Perfectionism is the enemy of good and some smart people might become perfectionists, spending too much time on one task, which can hinder their overall progress.

Prioritize physical health through regular exercise, a balanced diet, and adequate sleep. Physical well-being positively impacts cognitive function. Getting something like 10,000 paces in daily is a simple ritual that can help. Neglecting Self-Care because you are focused on intellectual pursuits can have a bad effect on your general health so keep this always in mind as you balance out your days.

Establish clear, achievable goals and track your progress. This provides motivation and direction for personal growth. However, keep in mind that setting unrealistic expectations and overly ambitious goals can lead to frustration when they’re not immediately achieved.

Embrace change and be willing to adapt to new technologies and methods. The ability to learn and adapt quickly is a key trait of smart individuals. Conversely, resistance to change and being attached to existing knowledge and methods can impede progress when better alternatives emerge.

Develop your emotional intelligence by understanding and managing your emotions and the emotions of others. This skill is crucial for success in various aspects of life. Recognize that a lack of empathy especially amongst highly intelligent individuals can harm relationships and limit success in teamwork and leadership roles.

Becoming progressively smarter requires a commitment to learning, adaptability, and self-improvement. Even naturally smart individuals can hinder their own progress by falling into the traps of arrogance, and perfectionism, and neglecting their well-being. It’s essential to strike a balance between leveraging natural intelligence and putting in the effort to continually grow and develop.

Intelligence

Intelligence is a multifaceted and complex concept that has intrigued intellectuals for centuries. Its definition, measurement, and understanding have evolved over time, and it continues to be a subject of debate and research.

Can it be viewed as a product, a process, content, or style? Why it is often described as encompassing all of these aspects?

Intelligence as a Product

One way to think about intelligence is as a product, an outcome, or a result of cognitive processes. This perspective is often associated with the idea of intelligence quotient (IQ) and standardized intelligence tests. IQ tests are designed to measure a person’s cognitive abilities and compare them to a standardized population and the distribution across that population. Scores on such tests are often considered a product of one’s intellectual abilities.

IQ tests, such as the Stanford-Binet or Wechsler Adult Intelligence Scale, are designed to assess a range of cognitive abilities, including logical reasoning, problem-solving, verbal comprehension, and mathematical skills. The scores derived from these tests are used to classify individuals into categories of intellectual ability, such as “average,” “above average,” or “below average.”

The product-oriented view of intelligence involves assigning numerical scores to individuals based on their performance on these standardized tests. This scoring allows for the comparison of individuals’ cognitive abilities, and it can be used for various practical purposes, such as educational placement and job selection.

However, it’s important to recognize the limitations of this perspective; standardized tests may not capture the full spectrum of human cognitive abilities, and they can be influenced by cultural and socioeconomic factors. They also do not account for other important aspects of intelligence, such as creativity, emotional intelligence, or practical problem-solving skills.

Intelligence as a Process

Intelligence is not static, it is dynamic and ever-evolving. If you take this perspective there is an emphasis on the cognitive activities and mental processes involved in thinking, learning, and problem-solving. From this viewpoint, intelligence is the ability to adapt to new situations, acquire knowledge, and make informed decisions.

Intelligence as a process encompasses a wide range of cognitive processes, including memory, perception, attention, reasoning, and problem-solving. These processes work together to enable individuals to gather information, process it, and use it to make decisions.

Intelligence also involves the capacity to learn from experience and adapt to changing circumstances. It is not solely determined by innate abilities but is influenced by factors such as education, exposure to new ideas, and the ability to apply knowledge effectively.

Viewing intelligence as a process also allows for an understanding of its development over one’s life. Children may develop cognitive skills at different rates, and most adults can continue to learn and adapt throughout their lives.

Recognizing intelligence as a process has practical implications for education and training. Effective teaching methods should consider the cognitive processes involved in learning and adapt instruction accordingly.

Intelligence as Content

Intelligence includes the content of knowledge and information that we possess at a point in time. This aspect of intelligence relates to what one knows and understands about the world. However, having knowledge alone does not necessarily equate to intelligence; intelligence also involves the ability to use and apply that knowledge practically and effectively.

The content-oriented perspective of intelligence acknowledges that individuals differ in the depth and breadth of their knowledge. Some people may have extensive knowledge in specific domains, such as mathematics, history, and art, while others may have a more general knowledge base.

Intelligence can be domain-specific, meaning that an individual may excel in one area of knowledge but not in others. For example, a person could be highly knowledgeable about music but less knowledgeable about science; this doesn’t make them particularly more or less intelligent, the assessment largely depends on what they are being assessed against and for what purpose.

Intelligence is not just about what one knows, therefore, but also about how effectively you can apply that knowledge to solve problems, make decisions, and navigate real-world situations. This ability to apply knowledge is a crucial aspect of practical intelligence.

Intelligence as Style

Cognitive styles refer to individual differences in how people approach and process information. Styles can be considered as aspects of intelligence because they influence how individuals think, learn, and solve problems. Different cognitive styles can be seen as different approaches to using one’s cognitive abilities.

The Analytical vs. Creative is an interesting way to think about style as some individuals have an analytical cognitive style, characterized by a preference for systematic and logical thinking. Others may have a creative cognitive style, which involves generating novel ideas and thinking outside the box. Both styles can be valuable in different contexts.

Another cognitive style relates to practical problem-solving. Some people may excel at finding efficient solutions to everyday challenges, the proverbial “MacGyver”, demonstrating a practical intelligence style. This is particularly valuable in real-world situations like sticky situations where coming up with imaginative ways to extricate oneself from the situation is essentially a show of intelligence.

Emotional intelligence is a distinct cognitive style that involves the ability to recognize, understand, and manage one’s own emotions and the emotions of others. This has become a very popular trait in the corporate world. Those who have high emotional intelligence are acknowledged as having an edge over those for whom the EQ is low. EQ plays a crucial role in social interactions and interpersonal relationships.

The “All Dimensions” intelligence

While each of these perspectives—intelligence as a product, process, content, and style—provides valuable insights into the nature of intelligence, it is essential to recognize that intelligence is complex and multidimensional. Intelligence cannot be fully captured by any one dimension alone. Instead, it is the integration of all or at least many of these dimensions; giving us a more comprehensive understanding of human intelligence.

A holistic view of intelligence acknowledges both cognitive abilities and the capacity to apply these abilities to real-world situations. Holistic assessment of intelligence recognizes that intelligence is not limited to a single aspect but involves a combination of cognitive processes, knowledge, cognitive styles, and practical problem-solving abilities.

Intelligence is highly context-dependent. What may be considered intelligent behavior in one situation may not be so in another. This contextual aspect of intelligence highlights the importance of adaptability and flexibility in using cognitive abilities effectively.

The variance among individuals, with some excelling in different aspects of intelligence witnesses the presence of some with superior analytical intelligence, while others are creative or practical. Recognizing and valuing these individual differences is crucial for fostering diversity and innovation especially when building teams.

Cultural and societal factors shape the way intelligence is defined and valued and certain aspects of intelligence are more highly valued over others, this leads to variations in what is considered “intelligent behaviour”.

Since intelligence is not fixed but can be developed and enhanced throughout one’s life, the educational and experiential opportunities offered to individuals often play a significant role in shaping and expanding an individual’s intelligence.

Inclusion vs Integration

Diverse needs hold significant importance in modern education for a multitude of compelling reasons. First and foremost, contemporary education places a strong emphasis on inclusivity and equity.

Inclusivity entails recognizing and addressing the diverse needs of students to ensure that all individuals, regardless of their backgrounds, abilities, or disabilities, have equal access to a high-quality education.

Such a focus on equity is aligned with the principles of social justice and human rights.

Legal and ethical obligations also play a pivotal role in emphasizing the consideration of diverse needs. Numerous countries have enacted laws and regulations that mandate educational institutions to provide equal educational opportunities for all students.

This includes the Individuals with Disabilities Education Act (IDEA) in the United States, which necessitates the provision of services and accommodations to meet the diverse needs of students. Complying with these legal obligations is an integral aspect of contemporary education.

In addition to legal imperatives, the realities of today’s world further underscore the significance of recognizing diverse needs. Globalization and cultural diversity have made schools more diverse than ever before, with students hailing from various cultural, linguistic, and socio-economic backgrounds. It is essential to understand and address the diverse needs of these students to foster cross-cultural understanding, tolerance, and effective communication in an interconnected global society.

Advancements in educational research and knowledge have also heightened the awareness of diverse needs. Developments in educational psychology and neuroscience have provided educators with a deeper understanding of how students learn. This knowledge has underscored the wide variability in learning styles, cognitive abilities, and neurological profiles among students. Consequently, tailoring instruction to meet diverse needs is crucial for enhancing learning outcomes.

Contemporary educational theories, such as Howard Gardner’s theory of multiple intelligences, acknowledge that intelligence is not confined to a singular dimension. Instead, students possess a range of strengths and abilities. Consequently, education should be adaptable to accommodate these diverse talents and aptitudes.

Preparing students for a diverse and inclusive workforce is another paramount goal of modern education. To thrive in today’s job market, students must develop skills in collaboration, problem-solving, and communication. Embracing diverse needs within the classroom helps students build these essential skills.

Education is not solely concerned with academic development; it also plays a pivotal role in shaping students’ moral and social growth. Recognizing and respecting diverse needs fosters empathy, tolerance, and social responsibility, contributing to the development of well-rounded citizens.

Inclusive education is seen as the gold standard for students with disabilities. It promotes their integration into mainstream classrooms, offering them opportunities for socialization and access to a more comprehensive curriculum. This, in turn, can significantly improve their long-term outcomes.

The expectations of parents and communities have also evolved to expect more. Parents and communities increasingly expect schools to provide inclusive education that caters to the diverse needs of their children which has led to higher expectations for educational institutions to implement them.

In education inclusion and integration are two distinct approaches for accommodating students with diverse needs.

Both approaches aim to provide an equitable and supportive learning environment, but they differ in their philosophies and practices. Additionally, there are nuanced alternatives that blend elements of both approaches.

Inclusion

Inclusion is a philosophy that advocates for the full and active participation of all students, including those with disabilities or special needs, in regular education classrooms and activities. It promotes the idea that every student has a right to be part of the general education setting.

This approach typically involves modifying the curriculum in teaching practice, teaching methods, and classroom arrangements to accommodate the diverse needs of all students. Support services, such as special education teachers or aides, may be provided within the regular classroom to help students with disabilities.

Prioritizing the creation of a diverse and accepting learning environment where students of all abilities learn together is the focus, for inclusion, the goal is to minimize segregation and promote social interaction among students.

Integration

Integration’s philosophy is to emphasize bringing students with disabilities into regular education classrooms on a temporary or partial basis. It may not necessarily involve a commitment to the full inclusion of all students, but rather a blending of students with and without disabilities for specific activities or lessons.

In practice, integrated settings are where students with disabilities may spend some of their time in regular classrooms and the rest in special education classrooms or resource rooms. The degree of participation in the general education setting can vary widely.

Integration focuses on providing students with disabilities access to the regular curriculum and social experiences to the extent deemed appropriate, while still acknowledging the existence of separate special education programs.

Alternative approaches

Inclusive Integration: This approach combines elements of both inclusion and integration. It recognizes that students have varying needs and abilities, so it allows for flexibility. Some students may spend most of their time in regular classrooms (inclusion), whilst others may participate in specific subjects or activities in a more specialized setting (integration).

Differentiated Instruction: involves tailoring teaching methods and content to meet the diverse needs of all students within a regular classroom. Teachers adjust their instruction to accommodate different learning styles and abilities, providing individualized support as needed.

Universal Design for Learning (UDL): UDL is a framework that promotes the design of educational materials, environments, and practices that are accessible to all students from the outset. It reduces the need for separate accommodations by creating inclusive learning experiences.

Co-Teaching: In co-teaching, a general education teacher and a special education teacher work together in the same classroom. This collaborative approach allows for a wide range of support within the regular classroom, catering to diverse needs.

Inclusion and integration represent different approaches to inclusive education, with inclusion being more focused on full participation and integration allowing for varying degrees of participation.

Some alternatives aim to strike a balance between these approaches to best meet the needs of diverse learners in an inclusive education setting. The choice of approach depends on the individual needs of students and the goals of the educational institution.

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