#DataCloud

[btambda]

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[govindhtech]

How Einstein 1 And Data Cloud Enable AI-driven Results

The artificial intelligence capabilities of Einstein 1 have already generated a great deal of hype and development, which will be a significant emphasis of Dreamforce 2024. A corresponding focus has also been observed on the Data Cloud, which is the mechanism that combines data from many sources to enable this AI magic. However, precisely how do the two cooperate? Does Einstein 1 need to be enabled with Data Cloud?

Data Unification: Data Cloud as the Basis

Salesforce has made significant investments in Data Cloud over the last few years. As a result, it went from being a mid-tier customer data platform to the Leader position in the Gartner Magic Quadrant for 2023. Ultimately, it is clear that inside the Salesforce ecosystem, Cloudera Data Platform (CDP) offers the strongest basis for a complete data solution.

Data Cloud absorbs and unifies data from throughout the company to release data that has become imprisoned. Data can be included and connected to the Salesforce data model with more than 200 native connectors, such as those for AWS, Snowflake, and IBM Db2. As a result, it may be used for analytics, Customer 360 profiles, marketing campaigns, and sophisticated AI features.

To put it simply, you can do more with your data the better it is. This necessitates a careful examination of the data prior to Data Cloud ingestion: Do you possess the information points required for customization? Do the various data sources employ the same formats required for sophisticated analytics? Are you able to train the AI models with enough data?

Recall that your teams will still require proper usage of the data after it has been imported and mapped in Data Cloud. This could entail using a “two in a box” approach to work with a partner in order to quickly absorb and put those lessons into practice. On the other hand, it necessitates extensive training, change management, and a readiness to embrace the new instruments. Teams must have documentation such as a “Data Dictionary for Marketers” in order to completely comprehend the data points they are utilizing in their campaigns.

Improved AI tools are offered by Einstein 1 Studio

Once Data Cloud is operational, you can utilize Einstein 1 Studio, which houses Salesforce’s most advanced and potent AI tools.

Salesforce’s low-code platform for integrating AI throughout its product line is called Einstein 1 Studio, and it can only be accessed through Data Cloud. Salesforce is making significant investments in the Einstein 1 Studio roadmap, and with each new release, the features get better. As of early September 2024, when this article is written, Einstein 1 Studio is made up of three parts:

Prompt builder

Salesforce users may integrate these generative AI capabilities into any item, including contact records, by creating reusable AI prompts with the prompt builder. AI commands such as record summarization, enhanced analytics, and suggested offers and actions are triggered by these prompts.

Copilot builder

Salesforce copilots are artificial intelligence interfaces that are generative and based on natural language processing. They are designed to enhance customer experiences and increase productivity, both internally and externally. In addition to triggering actions and updates using Apex and Flow, Copilot Builder lets you personalize the built-in Copilot functions with prompt builder features like summarizations and AI-driven search.

Model builder

Businesses can utilize the standard large language models from Salesforce by utilizing the Bring Your Own Model (BYOM) option. If they want to employ the ideal AI model for their company, they can also integrate their own, such as SageMaker, OpenAI, or IBM Granite. Furthermore, a new model can be constructed using Model Builder and reliable Data Cloud data.

How can you determine which model produces the greatest outcomes? You can test and validate responses with the BYOM tool, and you should also take a look at this model comparison tool.

As Salesforce continues to make significant investments in this field, expect to see frequent updates and new features.

Salesforce AI features in the absence of Data Cloud

If you haven’t yet utilized Data Cloud or absorbed a significant amount of data, Salesforce nevertheless offers a range of artificial intelligence functionalities. These can be accessed using Tableau, Sales Cloud, Service Cloud, Marketing Cloud, and Commerce Cloud. These built-in AI features include suggestions for products, generative AI content, and case and call summary. The potential for AI outputs increases with the quality and coherence of the data.

This is a really useful feature, and you ought to utilize Salesforce’s AI capabilities in the following ways:

Optimization of campaigns

Marketing campaign subject lines and message copy can be created using Einstein Generative AI, and Einstein Copy Insights can even compare the suggested copy to past campaigns to estimate engagement rates. This feature extends beyond Marketing Cloud; depending on CRM record data, it may also suggest AI-generated copy for Sales Cloud messages.

Recommendations

Based on CRM data, product catalogs, and past behavior, Einstein Recommendations can be utilized across clouds to suggest goods, information, and engagement tactics. The recommendation could take many different forms, such as customized copy depending on the situation or a recommendation for a product that is the next best offer.

Search and self-service

Based on the query’s natural language processing, past interactions, and a variety of tool data points, Einstein Search offers customized search results. Based on Salesforce’s foundation of security and trust, Einstein Article Answers can enable self-service by promoting responses from a chosen knowledge base.

Advanced analytics

Although Tableau CRM (previously Einstein Analytics), a specialized analytics visualization and insights tool, is available from Salesforce, Salesforce itself has AI-based advanced analytics capabilities built in. Numerous reports and dashboards, such as Einstein Lead Scoring, sales summary, and marketing campaigns, emphasize these business-focused advanced analytics.

AI, Data, CRM, and Trust

Salesforce offers strong tools within the Salesforce ecosystem thanks to its focus on Einstein 1 as “CRM + AI + Data + Trust.” The only way to improve these tools is to use Data Cloud as the primary tool for activating, combining, and aggregating data. You should anticipate considerably more improvement from this in the future. The AI industry is changing at an astonishing rate, and Salesforce is still setting the standard with its investments and methods.

Einstein 1 pricing

Pricing for Einstein 1 is offered in two editions:

Einstein 1 for Sales:

Cost: $500 per month for each user

Features: Consists of all the features found in Sales Cloud Unlimited Edition plus Data Cloud, Sales Planning, Maps, Revenue Intelligence, Generative AI, Enablement, Slack, and Slack Sales Elevate.

Einstein 1 for Service:

Cost: $500 per month for each user

Features: All the features of Service Cloud Unlimited Edition plus Data Cloud, Digital Engagement, Feedback Management, Self-Service, Slack, and CRM Analytics are included. Generative AI is also included.

Remember that these are list rates, and that actual pricing may change based on things like the quantity of users, the features that are needed, and any deals that may have been worked out.

Read more on Govindhtech.com

[archiuppu]

SALESFORCE DATA CLOUD EMPOWERING THE SUCCESS ACTIVITY

[conscendotechnologies]

Unveiling The Potential Of Salesforce Data Cloud Empowering Data-Driven Decision-Making

In today’s dynamic business landscape, data reigns supreme as a strategic asset driving innovation and competitive advantage. Recognizing the pivotal role data plays in business success, Salesforce introduces Data Cloud — a revolutionary platform within its extensive suite of offerings. Let’s delve into the intricacies of Data Cloud and explore how it empowers organizations to harness the full potential of their data assets.

Understanding Data Cloud Data Cloud stands as a cornerstone of Salesforce’s comprehensive suite, serving as a robust data platform that aggregates and integrates vast volumes of external data from diverse sources. This platform equips businesses with invaluable insights, enabling them to enrich customer profiles, enhance targeting capabilities, and make informed decisions across various operational functions.

Key Features and Capabilities 1. Data Enrichment: Data Cloud facilitates the enrichment of existing customer data by seamlessly integrating external sources such as demographic information, firmographics, and social media profiles. This enriched data provides organizations with a holistic view of their customers, enabling personalized and targeted marketing efforts.

2. Audience Segmentation: With Data Cloud, businesses can segment their customer base more effectively based on diverse criteria including demographics, behavior, and preferences. These segmented audiences pave the way for tailored marketing campaigns, resulting in heightened engagement and conversion rates.

3. Predictive Analytics: Leveraging advanced analytics capabilities, Data Cloud empowers organizations to uncover valuable insights and trends concealed within their data repositories. By identifying patterns and predicting future outcomes, businesses can make proactive decisions and stay ahead of market trends.

4. Integration with Salesforce Products: Data Cloud seamlessly integrates with other Salesforce products such as Sales Cloud and Marketing Cloud, ensuring a unified view of customer data across the organization. This integration fosters consistency, accuracy, and collaboration between different teams.

Real-World Applications Data Cloud finds applications across various industries, including:

Marketing Optimization: Businesses leverage Data Cloud to gain deeper insights into their target audience, personalize marketing messages, and optimize campaign performance.

Sales Enablement: Sales teams utilize enriched customer data to identify high-value prospects, prioritize leads, and tailor sales pitches for maximum impact.

Customer Service Enhancement: Customer service teams harness Data Cloud to access comprehensive customer profiles, anticipate needs, and deliver personalized support experiences.

Conclusion In the fiercely competitive business landscape, data emerges as a strategic asset that drives growth, innovation, and competitive advantage. Salesforce’s Data Cloud empowers organizations to unlock the full potential of their data assets, enabling smarter decision-making, enhanced customer experiences, and sustainable business success.

Whether you’re striving to enrich customer profiles, segment audiences, or unlock valuable insights, Data Cloud offers a comprehensive solution to meet your data needs. Embrace the power of Data Cloud and embark on a journey of data-driven decision-making in today’s digital era. www.conscendo.io

[unifydata]

94% of businesses believe they can extract more value from their data. Discover how @Salesforce Data Cloud makes this easy, offering actionable insights that help businesses achieve their goals. Learn why Data Cloud is leading the #CDP field: https://unify.agency/what-is-salesforce-data-cloud/

[getoncrm]

Data transformation awaits! Salesforce Data Cloud is your key to more intelligent business insights and AI-driven success. Swipe through our carousel to see how!

[s3groupasia]

Snowflake Data Cloud: Empowering Modern Data Analytics

Snowflake Data Cloud is a powerful cloud-based data platform that revolutionizes the way organizations manage and analyze their data. With its unique architecture and advanced capabilities, Snowflake enables businesses to harness the full potential of their data, making informed decisions and driving innovation at scale. By centralizing data management, facilitating collaboration, and supporting advanced analytics, Snowflake Data Cloud paves the way for organizations to thrive in the era of data-driven decision-making and innovation.

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Contact us now: https://endel.digital/weighmast/

[lumendata]

snowflake cloud services

What is Snowflake data cloud services ? 

The Snowflake on data platform is built as a layer over Amazon Web Services, Microsoft Azure, and Google cloud infrastructure. The business does not have to install specific hardware, and software instead it can use the support of in-house services. This makes it scalable and functions on a powerful architecture and data-sharing capabilities. Now since the platform separates the function of storage and computing, businesses can use and pay for both independently. Organizations with high storage demands but fewer CPU cycles and vice versa can thus tailor the platform to meet their needs accordingly. The data-sharing functionality also allows organizations to quickly share governed and secure data in real time.

The Snowflake architecture comprises: 

Database storage layer that holds both structured and semi-structured data which is organized as per file size, structure, compression, metadata, and statistics.

The compute layer, is a set of virtual warehouses that execute data processing tasks required for queries. Each warehouse or a cluster of them can access all the data in the storage layer without competing for computing resources.

The cloud services layer uses ANSI SQL and coordinates the entire system eliminating the need for manual data warehouse management and tuning. It includes services such as authentication, infrastructure management, metadata management, query parsing, and access control.  

Click on Snowflake Cloud Service to learn more.

[omnepresents]

Snowflake delivers the Data Cloud — a global network where thousands of organizations mobilize data with near-unlimited scale, concurrency, and performance. Inside the Data Cloud, organizations unite their siloed data, easily discover and securely share governed data, and execute diverse analytic workloads. Wherever data or users live, Snowflake delivers a single and seamless experience across multiple public clouds. Snowflake’s platform is the engine that powers and provides access to the Data Cloud, creating a solution for snowflake data warehousing, data lakes, data engineering, data science, data application development, and data sharing. Join Snowflake customers, partners, and data providers already taking their businesses to new frontiers in the Data Cloud.

[shanthababu]

ACID and BASE in Modern Data Engineering

Understand the ACID and BASE in Modern Data Engineering https://www.analyticsvidhya.com/blog/2022/12/understand-the-acid-and-base-in-morden-data-engineering/

#database #oraclecloud #oraclecloudinfrastructure #oracledeveloper #oracleuniversity #datacleaning #datacloud #databasedevelopment #datawarehousing #datawarehouses #datawarehousecloud #datawarehouses #gcpcloud #bigdataanalytics

[btambda]

Ambda's Mission is to deal with this, with care and reliability and to exhibit the highest value hidden deep inside your data assets.

[govindhtech]

Zero ETL-safe BigQuery-Salesforce Data Cloud integration

Zero ETL on Google cloud and Salesforce

The general availability of bidirectional data sharing between BigQuery and Salesforce Data Cloud excites us. Customers will be able to easily enhance their data use cases by safely merging data from several platforms, all without having to pay extra for complicated ETL (Extract, Transform, Load) pipelines and data infrastructure development.

More touchpoints and devices are available to provide instantaneous customer experiences, making prompt customer service more important than ever. However, as more data is generated, collected, and dispersed across SaaS apps and analytics platforms, it’s becoming harder

A partnership between Google Cloud and Salesforce was announced last year. According to the partnership, customers can easily combine data from both Salesforce Data Cloud and BigQuery, and can take advantage of the combined power of BigQuery and Vertex AI solutions to unlock and enrich new analytics and AI/ML scenarios.

They are making these features generally available today, allowing joint Google Cloud and Salesforce customers to safely access their data across various platforms and clouds. Consumers won’t need to set up or maintain infrastructure in order to access their Salesforce Data Cloud in BigQuery. They can also utilize their Google Cloud data to enhance Salesforce Customer 360 and other apps.

Customers of Salesforce and Google Cloud gain from these announcements in the following ways:

A single pane of glass and serverless, cross-platform data access requiring no ETL

Regulated and safe two-way access to their BigQuery and Salesforce Data Cloud data in almost real-time, without requiring the creation of data pipelines and infrastructure.

Enhance Salesforce Customer 360 and Salesforce Data Cloud with their Google Cloud data. Additionally, the capacity to enhance client data with minimal data movement by combining it with other pertinent public datasets.

utilizing unique Vertex AI and Cloud AI services for churn modeling, predictive analytics, and returning to customer campaigns via the integration of Vertex AI and Einstein Copilot Studio.

BigQuery Omni and Analytics Hub allow customers to view their data holistically across the Salesforce and Google platforms, spanning cloud boundaries. With the help of this integration, data scientists, marketing analysts, and other data and business users can now combine data from the Google and Salesforce platforms to conduct AI/ML pipelines, analyze data, and gain insights in a self-service manner without the assistance of infrastructure or data engineering teams.

Customers can concentrate on analytics and insights because this integration is completely managed and governed, and it spares them from a number of significant business difficulties that often arise when integrating important enterprise systems. These innovations uphold the data governance and access policies that administrators have established. Access to datasets is restricted to those that have been expressly shared, and only those with permission can exchange and examine the information. Relevant data is pre-filtered from Salesforce Data Cloud to BigQuery with minimal copying, lowering egress costs and data engineering overhead when data is spread across multiple clouds and platforms.

Simple and safe access from Google Cloud to Salesforce Data Cloud

Consumers want to be able to access and integrate their loyalty and point-of-sale data from Google analytics platforms with their marketing, commerce, and service data from Salesforce Data Cloud to gain actionable insights about their customer behavior, such as likelihood to buy, cross-sell/upsell recommendations, and the ability to run highly customized promotional campaigns. Additionally, they wish to use unique Google AI services to create machine learning models for training and predictions on top of combined Salesforce and Google Cloud data. This will enable use cases like price elasticity, market-mix modeling, churn modeling, customer funnel analysis, and A/B test experimentation.

Customers can now easily access their Salesforce Data Cloud data with the launch of unique BigQuery cross-cloud and data sharing features. They have access to all the pertinent data required to run powerful ad campaigns and conduct cross-platform analytics securely with other Google products. Administrators of Salesforce Data Cloud can quickly and easily share data with the appropriate BigQuery users or groups. Through the Analytics Hub UI, BigQuery users can effortlessly subscribe to shared datasets.

With this platform integration, information can be shared in multiple ways:

You can use a single cross-cloud join of your Salesforce Data Cloud and Google Cloud datasets for smaller datasets and ad hoc access, such as to identify the store with the highest sales last year, with little data movement or duplication.

You can use cross-cloud materialized views to access larger data sets that power your executive update, weekly business review, or marketing campaign dashboards. These views are automatically and incrementally updated, bringing in new data only on a periodic basis.

Add Google Cloud-stored data to Salesforce Customer 360

They also hear from customers, particularly retailers, who want to use the rich features of Salesforce Data Cloud to deliver personalized messaging, create a more comprehensive customer 360-degree profile, and access and combine behavioral data from their websites and mobile apps that was collected by Google Analytics with their own data. Breaking down data silos and providing customers with seamless real-time access to Google Analytics data within Salesforce Data Cloud to create more detailed customer profiles and personalized experiences is now easier than ever.

Customers of Salesforce Data Cloud can connect to their Google Cloud account with ease using point-and-click navigation, choose pertinent BigQuery datasets, and make them available as External Data Lake Objects, enabling real-time data access. After becoming Data Lake Objects, they function as native Data Cloud objects, enhancing Customer 360 data models and providing insights to support Analytics and Personalization for Customer 360 models. The operational overhead and latency associated with the conventional ETL copy approach are eliminated by this integration, which also removes the need to create and maintain ETL pipelines for data integration.Imagec redit to Google cloud

Tearing down the barriers separating Google and Salesforce data

With the help of this platform integration between Google Cloud and Salesforce Data Cloud, businesses can now break down data silos, obtain actionable insights, and provide outstanding customer service. Through the power of Google AI, unified access, and seamless data sharing, this partnership is revolutionizing how businesses use their data to achieve success.

Customers can directly access data stored in Salesforce Data Cloud and combine it with data in Google Cloud to further enrich it for business insights and activation through the unique cross-cloud functionality of BigQuery Omni and the data sharing capabilities of Analytics Hub. Customers no longer need to build custom ETL or move data in order to perform unmatched cross-cloud analytics or view their data across clouds.

Read more on govindhtech.com

[watchingmywork]

People Analytics: The Key to Unlocking Your Business Potential

Imagine if you could unlock your business's hidden potential with the power of data—not just numbers and spreadsheets, but deep insights into your organization's most valuable asset: your employees.

In today’s rapidly evolving business landscape, success isn’t just about having the right product or strategy; it’s about having the right team working in the right way. As a result, people analytics comes into play, transforming and altering how businesses manage their staff.

It turns employee data into a goldmine of actionable insights, helping organizations hire smarter, engage their workforce more effectively, and optimize performance. It’s more than just an HR tool. It’s a strategic advantage that drives growth, innovation, and success.

Ready to tap into this game-changing approach? Let’s explore how to unlock your business's true potential.

What is People Analytics?

This analytics is the process of using data to gain insights into various aspects of the workforce, such as employee performance, engagement, and overall organizational health. Also known as HR or workforce analytics, this data-driven approach involves gathering and evaluating employee-related metrics, including hiring trends, turnover rates, and productivity levels. By turning raw data into meaningful insights, it enables businesses to make informed decisions that optimize their workforce, improve business outcomes, and boost employee productivity.

The Benefits of People Analytics

Integrating this into a company's strategy gives several valuable benefits:

Improved Hiring and Talent Management

It revolutionizes hiring by using data to identify the traits of successful employees, leading to smarter recruitment decisions. It also helps manage talent by pinpointing skill gaps and high-potential individuals, enabling personalized development plans and better employee growth. This method reduces turnover and ensures a more efficient and skilled workforce.

Increased Employee Engagement and Retention

It enhances employee engagement by identifying and addressing factors that lead to dissatisfaction. By understanding the drivers of disengagement, companies can make targeted improvements, leading to greater job satisfaction and lower turnover rates. This proactive approach not only keeps employees motivated but also reduces the costs and disruptions associated with frequent staff changes.

Enhanced Productivity and Performance

It helps businesses increase productivity by identifying trends and inefficiencies in work processes. Companies can use performance data to optimize processes, remove productivity obstacles, and improve team dynamics. This data-driven strategy improves workflows, resulting in greater efficiency and a more productive workforce.

Data-Driven Decision Making

It improves decision-making by replacing guessing with reliable facts. It enables businesses to make decisions based on genuine information, whether they are enhancing pay plans, scheduling organizational changes, or maximizing resource allocation. This method reduces risks and ensures that decisions are aligned with strategic goals, resulting in more accurate and effective outcomes.

Popular People Analytics Tools

Here are trendy tools:

EmpMonitor: Provides detailed insights into workforce behavior, helping businesses track performance and productivity.

Workday: Provides comprehensive HR analytics and reporting capabilities, integrating data from various HR functions to offer insights into workforce trends, performance, and engagement.

SAP SuccessFactors: Offers advanced analytics features that help organizations analyze employee data, manage talent, and track key metrics for better decision-making and strategic planning.

ADP DataCloud: Delivers powerful analytics for workforce data, helping businesses understand trends, optimize HR processes, and improve employee experience and performance.

Tableau: Allowing organizations to create custom dashboards and analyze workforce data in depth.

Visier: Providing actionable insights into employee performance, retention, and engagement.

Also, watch this video - How to Set Productivity Rules On EmpMonitor

Final Thoughts

People analytics is no longer a luxury reserved for large corporations; it is a necessity for businesses looking to stay competitive in the modern landscape. By harnessing the power of data, organizations can unlock valuable insights into their workforce, improve employee engagement and retention, and drive productivity. With advanced people analytics tools, businesses have exceptional access to insights that drive success. Ultimately, It is the key to unlocking your business potential, enabling smarter decisions and better outcomes in every aspect of the organization.

[certspots]

Salesforce Data Cloud Consultant Certification Dumps Questions#datacloud

[unifydata]

Big news! Salesforce has grabbed the top spot in the Gartner Magic Quadrant 2024 for CDPs. It's more than just a win; it's a new benchmark for competing vendors. Dive into our thoughts on why Salesforce's Data Cloud is a game-changer and how it gained a leader position: https://unify.agency/gartner-magic-quadrant-2024/ The Gartner Magic Quadrant 2024.