Data Governance Archives - gettectonic.com - Page 3
Einstein in Salesforce

Einstein in Salesforce

Salesforce AI and CRM Evolution Salesforce has long been a leader in customer relationship management (CRM) by pioneering cloud technologies. Recently, the platform has significantly advanced with the integration of generative artificial intelligence (AI) and AI-powered features, thanks to its Einstein technology. Einstein in Salesforce is like a super smart computer overseeing and analyzing the data in your CRM. This guide explores Salesforce’s AI strategy, exploring its specific products and features to help business teams understand and benefit from this technology. Exploring Salesforce’s Advanced AI Features Einstein, Salesforce’s AI technology, powers various advanced features within the platform. This guide will cover these capabilities, provide real-life adoption examples, and discuss their benefits. Additionally, it offers best practices, solutions, and services to facilitate your Einstein implementation. Salesforce’s Comprehensive CRM Solution Salesforce remains a number one in the CRM software world, offering robust solutions for managing relationships across various departments. Specific clouds within Salesforce enable teams to handle marketing, sales, customer service, e-commerce, and more. The platform focuses on customer experience and provides robust data analytics to support decision-making. Enhancements Through Generative AI Salesforce’s generative AI has rapidly enhanced the platform’s automation, workflow management, data analytics, and assistive capabilities for customer management. A prime example is Salesforce Copilot, which aids internal users with outreach and analysis tasks while improving the external user experience. What is Salesforce Einstein? Salesforce Einstein is the first comprehensive AI for CRM, integrating AI technologies to enhance the Customer Success Platform and bring AI to users everywhere. It is seamlessly integrated into many Salesforce products, offering generative AI built specifically for CRM. Key Features of Salesforce Einstein Comprehensive AI Capabilities of Salesforce Einstein Einstein extends its capabilities across the Salesforce CRM platform under the Customer 360 umbrella, enhancing intelligence and providing personalized customer experiences. Key Benefits of Salesforce Einstein Salesforce Einstein helps close deals faster, personalize customer service, understand customer behaviors, target audience segments better, and create personalized shopping experiences. It ensures data protection and privacy through the Einstein Trust Layer, maintaining strong data governance controls. Responsible AI Principles Salesforce is committed to responsible AI principles, ensuring Einstein is trustworthy and safe for every organization. Organizations can select from various principles to ensure ethical AI use in their operations. Implementation of Salesforce Einstein Salesforce Einstein is a powerful AI solution transforming how businesses interact with customers. By leveraging machine learning and data analysis, it personalizes experiences, predicts customer behavior, and automates tasks, boosting sales, enhancing service, and driving growth. As AI evolves, its impact on CRM will continue to grow, making it an indispensable tool for businesses aiming to stay competitive in today’s data-driven landscape. Top 4 Benefits of Salesforce Einstein in an Organization Einstein Essentials Salesforce Einstein and GPT (Generative Pretrained Transformer) technologies represent significant advancements in AI, particularly in CRM and natural language processing. Here’s a brief overview of their relevance and potential intersection: Data Handling and Ethics in Salesforce Salesforce manages a vast amount of customer data, and the ethical handling of this data is crucial. Key considerations include data privacy, secure storage, access controls, compliance with regulations like GDPR and CCPA, and the ethical use of AI and machine learning. It’s important to maintain transparency, avoid biases, and ensure AI models are making ethical decisions. Newest Einstein Features for 2024 In the rapidly evolving ecosystem of Salesforce, AI offers a suite of tools to spark innovation, streamline operations, and provide richer business insights. Explore these potentials and let Einstein AI reshape your work in 2024. Content updated June 2024. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

Read More
Big Data and Data Visualization

Big Data and Data Visualization Explained

Data Visualization: Turning Complex Data into Clear Insights Data visualization is the practice of converting information into visual formats, such as maps or graphs, to make data more accessible and understandable. The primary purpose of data visualization is to highlight patterns, trends, and outliers within large data sets, allowing users to quickly glean insights. The term is often used interchangeably with information graphics, information visualization, and statistical graphics. The Role of Data Visualization in Data Science Data visualization is a crucial step in the data science process. After data is collected, processed, and modeled, it must be visualized to draw meaningful conclusions. It’s also a key component of data presentation architecture, a discipline focused on efficiently identifying, manipulating, formatting, and delivering data. Importance Across Professions Data visualization is essential across various fields. Teachers use it to display student performance, computer scientists to explore AI advancements, and executives to communicate information to stakeholders. In big data projects, visualization tools are vital for quickly summarizing large datasets, helping businesses make informed decisions. In advanced analytics, visualization is equally important. Data scientists use it to monitor and ensure the accuracy of predictive models and machine learning algorithms. Visual representations of complex algorithms are often easier to interpret than numerical outputs. Historical Context of Data Visualization Data visualization has evolved significantly over the centuries, long before the advent of modern technology. Today, its importance is more pronounced, as it enables quick and effective communication of information in a universally understandable manner. Why Data Visualization Matters Data visualization provides a straightforward way to communicate information, regardless of the viewer’s expertise. This universality makes it easier for employees to make decisions based on visual insights. Visualization offers numerous benefits for businesses, including: Advantages of Data Visualization Key benefits include: Challenges and Disadvantages Despite its advantages, data visualization has some challenges: Data Visualization in the Era of Big Data With the rise of big data, visualization has become more critical. Companies leverage machine learning to analyze vast amounts of data, and visualization tools help present this data in a comprehensible way. Big data visualization often employs advanced techniques, such as heat maps and fever charts, beyond the standard pie charts and graphs. However, challenges remain, including: Examples of Data Visualization Techniques Early computer-based data visualizations often relied on Microsoft Excel to create tables, bar charts, or pie charts. Today, more advanced techniques include: Common Use Cases for Data Visualization Data visualization is widely used across various industries, including: The Science Behind Data Visualization The effectiveness of data visualization is rooted in how humans process information. Daniel Kahneman and Amos Tversky’s research identified two methods of information processing: Visualization Tools and Vendors Data visualization tools are widely used for business intelligence reporting. These tools generate interactive dashboards that track performance across key metrics. Users can manipulate these visualizations to explore data in greater depth, and indicators alert them to data updates or important events. Businesses might use visualization of data software to monitor marketing campaigns or track KPIs. As tools evolve, they increasingly serve as front ends for sophisticated big data environments, assisting data engineers and scientists in exploratory analysis. Popular data visualization tools include Domo, Klipfolio, Looker, Microsoft Power BI, Qlik Sense, Tableau, and Zoho Analytics. While Microsoft Excel remains widely used, newer tools offer more advanced capabilities. Data visualization is a vital subset of the broader field of data analytics, offering powerful tools for understanding and leveraging business data across all sectors. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

Read More
Having An Effective AI Strategy

Having An Effective AI Strategy

It All Begins with Strategy A robust AI strategy is the cornerstone of successful AI implementation. It provides clarity on vision, purpose, short and long-term goals, and necessary steps for the entire organization. Rooted in data, this strategy should include measurable objectives and KPIs to foster seamless collaboration across teams. As with any strategic initiative, it starts with trustworthy data. Having An Effective AI Strategy. Keys to Having An Effective AI Strategy Prepare Your Data Define Business Goals Identify and Prioritize Use Cases Establish Data Governance Policies Check Your Technology Stack Emphasize Continuous Improvement Start Small Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

Read More
Cloud Analytics

Cloud Analytics Explained

Understanding Cloud Analytics Cloud analytics refers to leveraging cloud computing resources to conduct data analysis more efficiently. It involves using advanced analytical tools to extract insights from vast datasets, presenting information in a user-friendly format accessible via web browsers. Core Concepts of Cloud Analytics Explained Cloud analytics shifts traditional data analytics operations, such as processing and storage, to public or private cloud environments. Similar to on-premises analytics, cloud solutions facilitate pattern identification, predictive modeling, and business intelligence (BI) insights. They leverage cloud technologies and algorithms, notably artificial intelligence (AI), including machine learning (ML) and deep learning (DL). Operational Framework of Cloud-Based Analytics Cloud analytics platforms offer capabilities to build, deploy, scale, and manage data analytics solutions in a cloud-based infrastructure. Examples include cloud enterprise data warehouses, data lakes, and on-demand BI and marketing analytics. Users can subscribe to services under flexible pricing models, alleviating concerns about scalability, performance, and maintenance. Types of Cloud Analytics Cloud-based analytics solutions vary by deployment model: Key Features and Benefits Cloud analytics offers several advantages: Applications and Use Cases Cloud analytics supports diverse applications, including: Comparing Cloud Analytics with Traditional Data Analytics Cloud analytics leverages cloud infrastructure for scalable and flexible data processing, contrasting with traditional analytics tools deployed on-premises. This shift enhances agility and accessibility while reducing operational complexities and costs. Why Cloud Analytics Matters Cloud analytics empowers organizations to harness actionable insights efficiently, driving informed decision-making and competitive advantage. It streamlines operations, fosters collaboration, and enhances data reliability and strategic planning capabilities. Adopting cloud-based analytics enables businesses to transform data into valuable intelligence, fueling innovation and growth. By leveraging cloud-based resources, organizations can achieve operational excellence, secure data-driven insights, and maintain a competitive edge in today’s dynamic business landscape. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

Read More
Salesforce role hierarchy

What is a Salesforce Data Dictionary?

What is a Salesforce Data Dictionary? A Salesforce data dictionary functions as a comprehensive repository containing names, attributes, and descriptions of data objects or business logic within a data model. Its primary purpose is to ensure consistency in the terminology used by business users or stakeholders, particularly regarding type/category, such as personally identifiable information (PII). This user-friendly and business-centric solution allows organizations to document and establish a shared vocabulary for their use of Salesforce, facilitating the simplification of processes through just-in-time learning solutions like Spekit. Components of a Data Dictionary A data dictionary serves as a centralized metadata repository where all CRM changes are documented, enabling quick impact analysis and future changes without concerns about system breaks. It compiles and communicates the structure and content of data, offering meaningful descriptions for individually named data objects. Benefits of a Salesforce Data Dictionary Clear Metadata Across Teams Understanding Field Accessibility to Sensitive Data Reduce Technical Debt Avoid Unintended Breaks Trust the Integrity of Your Business Reports How to Create a Data Dictionary in Salesforce To create a data dictionary in Salesforce, follow these steps: Difference Between Metadata and Data Dictionary The data dictionary contains data about the data in the database, while metadata is the data about the data in the data warehouse. These terms are commonly used and play distinct roles. Types of Data Dictionary There are two types of data dictionaries: active and passive. An active data dictionary is tied to a specific database and updates automatically with the data management system. Benefits of Data Dictionary The benefits of a data dictionary include faster detection of data anomalies, improved data quality, availability of trustworthy data, greater transparency within data teams, better regulatory compliance, and faster analytics. Content updated July 2023. Like2 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

Read More
safeguarding personal information

Be Careful With My Data

Aware of the escalating significance of data protection in the digital age, customers are becoming increasingly vigilant about safeguarding their personal information. However, amidst this heightened awareness, companies have an opportunity to earn and maintain trust by providing clear and transparent explanations of how they intend to use customer data. Gone are the days when customers passively accept vague assurances buried within lengthy user agreements. Today, they demand transparency and accountability regarding data usage, driven partly by a general sense of skepticism towards companies that may not always prioritize customer benefits when leveraging data. Indeed, not all data is perceived equally by customers. While there’s a growing comfort level with companies collecting first-party data directly from their platforms, such as website clicks or interactions, there’s often greater apprehension about third-party data sourced from external data brokers. This disparity in perception underscores the importance of companies being mindful of the origin and nature of the data they collect, respecting customer preferences, and ensuring transparent data practices. Amidst the evolving landscape of data protection, the imperative for securing sensitive personal information has never been more critical. What was once solely a concern for businesses has now become a shared responsibility for consumers and individuals alike. With an abundance of information available on data protection measures, ranging from safeguarding passwords and financial details to protecting devices from hackers and malware, individuals are inundated with advice. Yet, navigating this sea of information can be daunting, especially for those less technologically savvy. In response to this challenge, we’ve compiled a comprehensive list of 32 simple and practical tips for enhancing data security and protecting personal information. These tips encompass a wide array of measures, including encrypting data, backing up data regularly, ensuring the permanent deletion of old computer hard drives, securing wireless networks, using firewalls, and encrypting data on removable storage devices like USB drives and SIM cards. Furthermore, our list provides guidance on protecting data while working remotely, covering topics such as using virtual private networks (VPNs), maintaining physical control over devices, employing personal hotspots, separating personal and work devices, and implementing cybersecurity policies. Additionally, it delves into security best practices for video conferencing, identifying and avoiding phishing emails, installing antivirus and malware protection, and securely disposing of old IT equipment and records. By adopting these practical measures, individuals and businesses can fortify their defenses against cyber threats and data breaches, thereby safeguarding personal information and preserving trust with customers. In an era where data privacy is paramount, proactive steps towards data protection not only mitigate risks but also demonstrate a commitment to ethical and responsible data practices. As technology continues to evolve, cultivating a culture of data security and privacy awareness remains essential for fostering trust and confidence in the digital ecosystem. Keeping your passwords, financial, and other personal information safe and protected from outside intruders has long been a priority of businesses, but it’s increasingly critical for consumers and individuals to heed data protection advice and use sound practices to keep your sensitive personal information safe and secure. There’s an abundance of information out there for consumers, families, and individuals on protecting passwords, adequately protecting desktop computers, laptops, and mobile devices from hackers, malware, and other threats, and best practices for using the Internet safely. But there’s so much information, from using a virtual private network (VPN) to using unique and strong passwords or an antivirus software, it’s easy to get confused, particularly if you’re not tech-savvy. We’ve compiled a list of 101 simple, straightforward best practices and tips for keeping your family’s personal information private and protecting your devices from threats. Securing Your Devices and Networks 1. Encrypt your data Data encryption isn’t just for technology geeks; modern tools make it possible for anyone to encrypt emails and other information. “Encryption used to be the sole province of geeks and mathematicians, but a lot has changed in recent years. In particular, various publicly available tools have taken the rocket science out of encrypting (and decrypting) email and files. GPG for Mail, for example, is an open source plug-in for the Apple Mail program that makes it easy to encrypt, decrypt, sign and verify emails using the OpenPGP standard. And for protecting files, newer versions of Apple’s OS X operating system come with FileVault, a program that encrypts the hard drive of a computer. Those running Microsoft Windows have a similar program. This software will scramble your data, but won’t protect you from government authorities demanding your encryption key under the Regulation of Investigatory Powers Act (2000), which is why some aficionados recommend TrueCrypt, a program with some very interesting facilities,” explains John Naughton in an article for The Guardian. Twitter: @guardian 2. Backup your data One of the most basic, yet often overlooked, data protection tips is backing up your data. Basically, this creates a duplicate copy of your data so that if a device is lost, stolen, or compromised, you don’t also lose your important information. As the U.S. Chamber of Commerce and insurance company Nationwide points out, “According to Nationwide, 68% of small businesses don’t have a disaster recovery plan. The problem with this is the longer it takes you to restore your data, the more money you’ll lose. Gartner found that this downtime can cost companies as much as $300,000 an hour.” Twitter: @growwithco 3. Make your old computers’ hard drives unreadable Much information can be gleaned through old computing devices, but you can protect your personal data by making hard drives unreadable before disposing of them. “Make old computers’ hard-drives unreadable. After you back up your data and transfer the files elsewhere, you should sanitize by disk shredding, magnetically cleaning the disk, or using software to wipe the disk clean. Destroy old computer disks and backup tapes,” according to the Florida Office of the Attorney General. Twitter: @AGPamBondi 4. Secure your wireless network at your home or business A valuable tip for both small business owners and individuals or families, it’s always recommended to secure your

Read More
Salesforce BI

Protecting Your Salesforce Data

The landscape of Salesforce has undergone significant growth beyond its humble CRM origins, yet assumptions about the data within Salesforce orgs often remain unchanged.  This is crazy when you think about the original Customer Relationship Management system and how many apps it had to connect to in order to actually manage your customer relationships.   Protecting your Salesforce data is everyone’s responsibility. It is good to rethink how Salesforce data is used, especially considering its increasing indispensability in tandem with the platform’s expansion into diverse business processes and industries. The discontinuation of Salesforce’s data recovery service further creates the need for an updated perspective. Protecting Your Salesforce Data Salesforce Backup. Protect your enterprise against data loss and corruption. Contact Tectonic today. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

Read More
Salesforce Data Studio

Salesforce Data Studio

Data Studio Overview Salesforce Data Studio is Salesforce’s premier solution for audience discovery, data acquisition, and data provisioning, offering access to the world’s largest premium data ecosystem. It provides: Data Studio is a self-service platform that connects data owners and buyers directly, fostering new opportunities for audience discovery, sharing, and activation. Leading brands like Anheuser-Busch, Conagra, Essence, and Heineken leverage Salesforce Data Studio to enhance the value of their data and drive revenue. Announcing Salesforce Data Studio Salesforce Data Studio addresses the shortcomings of traditional data exchanges and marketplaces. Unlike legacy platforms that rely on intermediaries, Data Studio allows data owners to maintain control and transparency. The platform ensures secure transactions with comprehensive data governance tools, enabling precise control over data access, usage, and duration. Key Features of Salesforce Data Studio: Industry Reactions Salesforce Marketing Cloud: The Leader in Digital Marketing Salesforce Marketing Cloud enables marketers to deliver connected, personalized, and real-time consumer engagement across all channels globally. With Marketing Cloud Einstein, marketers can harness artificial intelligence to optimize timing, channel, content, and audience for their marketing messages. Brands like Dunkin’ Donuts and Nestle Waters rely on Marketing Cloud to enhance engagement and advance their business goals. On average, companies using Marketing Cloud see a 27% increase in campaign effectiveness and a 26% boost in marketing ROI. Pricing and Availability Salesforce Data Studio is available now in several editions: The new Audience Discovery and Search feature will be available starting November 2017. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

Read More
gettectonic.com