Jump-Start your Analytics Journey with Einstein Analytics Templates

Implementing a meaningful analytics application or even a dashboard from scratch with the right level of information can be a tedious and confusing process. You can keep going back and forth with the users trying to figure out the level of details that needs to be presented to the audience and also at the same time lose track of the objectives while trying to come up with visualizations that ring a bell with the consumers of the dashboard.

 

While the presentation layer takes most of the attention, the underlying data preparation and data processing required for the visualizations can be even more challenging.

 

Introducing Einstein Analytics Templates

 

Salesforce has a curated gallery of prebuilt Analytics Template Apps that can help make the whole process effortless and effective. The templates not only provide expert data analysis but also come packed with the required back end plumbing to get the right level of information from your Salesforce Orgs.

 

Einstein Analytics template apps provide a set of Dashboards, Lenses with supporting Datasets and Dataflows that serve as a starting point for Einstein Analytics Admins and Developers to start building their requirements. Using the pre-built template apps as the base for custom development not only enables you to deliver analytics apps faster to business users but also helps in building engaging visualizations with the right level of details.

 

The prebuilt template apps also form excellent demo material that can be used to present creative ideas to the business community using best in class dashboards and visualizations.

 

The Template Gallery

Several Einstein Analytics templates apps are provided by Salesforce addressing different industry needs and also by partners who have developed Einstein Analytics Apps using their expertise. The template apps are easily accessible using the Templates Gallery, App Exchange and can be installed using just a few clicks. A broad level categorization of the Einstein Analytics templates include the following types:

  • Cloud Based Templates like Sales, Service, Marketing, Field Service Lightning, Financial Services and Healthcare.
  • Focussed Business and Industry Templates like Revenue Operations, Social Case Analytics, Lead Trending, Wealth Management, Subscription Analytics, Quote Analytics, Patient Risk Stratification and Insurance Analytics templates to name some.
  • Productivity Templates like Adoption Analytics template, Approval Analytics template, Event Monitoring Analytics App and Change Analytics App.

 

Installation of Template Apps

 

Einstein Analytics Templates can be very easily installed from the Template Gallery by following the below steps. Note: Some of the templates may have additional questions that need answering in the wizard to meet the data requirements of the template.

  • Open the Template Gallery from Analytics Studio by clicking the Template Gallery link.
  • Search for the template you want to install or filter the list by selecting values from the Filter dropdown. The Filter dropdown helps filtering the template list by using Tags and Industry values.

  • Select the template and depending upon the template the wizard may present a set of questions. These questions are required by the template to generate the visualizations and outcomes based on the type of template.

 

  • After completing the questionnaire the template installation process will start and the status of the installation will be displayed in a new tab.

 

  • Once the installation is complete, you are all set to use the brand new template app. The app will be available in the Apps section of Analytics studio.
  • Click the ‘Run’ button to test drive your new template app.

Templates will not only make the whole process for efficient and easy for you but also make your solution more effective with the following:

  • Use of best in class visualizations and data representations
  • Inclusion of industry expertise through specialized industry templates with actionable insights
  • Standardized prebuilt datasets, dataflows and backend development to pull the required data.

So next time you are starting on an Einstein Analytics solution, do not miss on the opportunity to amaze your users by delivering a stunning app at lightning speed using Einstein Analytics Templates.

Aethereus is now recognized as a Salesforce Gold Partner

Aethereus, a rapidly growing Salesforce boutique, with offices in USA and India,  is excited to announce that it received Gold Consulting Partner status on 01-September, 2020 from Salesforce. Founded in July 2019, Aethereus became Salesforce Registered Partner in September 2019 and achieved Silver status in just 3 months’ time in December 2019. And now, Aethereus is one of the fastest to achieve the Gold Partnership status in less than a year of becoming a Salesforce partner.

 

Securing a Gold status in Salesforce Partnership program requires a company to meet stringent milestones and demonstrate an exceptional level of client engagement, employee expertise and client success. In little more than a year since its inception, Aethereus has worked with some of the marquee clients like WhiteHat Jr. (Byju’s), Mintifi, GoQuest etc., created a pool of 45+ resources and received ‘All Star’ (5/5) CSAT score for all the projects delivered on Salesforce AppExchange.

 

Vijay Gupta, Co-Founder, CTO & Head of Alliances, Aethereus stated “Becoming a Gold Salesforce Partner in a record time, is a significant milestone in our journey. It is a testament to our unique business model, that is focused on agility and delivering meaningful outcomes to our Customer. We are proud of the superb execution by Team Aethereus over the past 1 year and owe our success to this team

With 30+ logos and 24+ 5/5 CSAT scores on AppExchange, we are setting our sights on deepening our investments in the India market with specific focus on Financial Services, Manufacturing and Education segments.”

 

Aethereus Perspectives : Reimagine Customer Experience in Lending

The last decade has seen an immense technological disruption across industries, including finance. Only a few years ago, digital lending was dismissed as a mere “buzzword”, but the exponential growth of fintechs in the sector has resolved all such doubts. BCG has estimated that India’s digital lending market will grow from ₹ 3.9 trillion in 2018 to ₹ 24 trillion by 20231. This would make the share of digital lending at 48 % of the overall lending market.2 Customer expectations have grown due to what is called the ” Amazon Effect”, and financial institutions are struggling to keep up and provide a frictionless user experience. They need to think beyond “minimizing the number of clicks” & transform all their current processes to better accommodate a digital savvy customer. According to a research, 75% of MSMEs in India are comfortable with sharing data digitally3. Data, advanced analytics & AI can thus be leveraged to eliminate steps & improve processes.

Disrupting through innovative models

Fintechs have pioneered new models of doing business to disrupt the lending space by making their processes more customer-centric. A few examples of models that are gaining foothold in the market are as follows-

  • PoS based Lending- Since 47% MSMEs have adopted digital tools for accounting, payments & sales4, data from PoS machines of merchants , like credit/debit card swipes & online sales can be used to offer unsecured loans . For example, NeoGrowth offers a unique product to SMEs by using PoS data for underwriting loans, coupled with an option of automatic daily repayments.
  • Data aggregator based business loans– Fintechs like Indifi offer loans tailored for specific segments such as travel, restaurants, e-commerce by using data from data aggregators like MakeMyTrip or Swiggy to assess the risk profile of the borrower. For example, a small restaurant can avail a loan on the basis of its transactions & customer ratings with Swiggy and Zomato
  • Mobile-data based lending– Few fintechs like Capital Float use applicant’s mobile data such as banks transaction SMS history, mobile recharge information & call patterns to assess creditworthiness of borrowers.
  • Invoice financing- Short-term working capital needs of businesses are financed by fintechs like KredX, who extend loans by discounting unpaid invoices to a network of banks, NBFCs, wealth managers etc. When the invoice is successfully paid, the full amount gets credited to the investors directly.
  • Marketplaces– Fintechs such as Paisabazaar not only meet financial needs of consumers but also provide them with a choice of the financial institution they want to avail a loan from . It offers consumers a seamless end-to-end digital experience & is popular with millennials who can fulfill their “impulse purchase” & ” emergency fund” needs.
  • P2P Lending- Digital marketplaces like Faircent connect borrowers with lenders allowing quick access to low-cost loans at affordable costs.

An Enabling Regulatory Environment

The Indian regulatory environment has evolved rapidly in the past few years, providing a favorable environment for the growth of fintechs. Few initiatives that have improved the company’s digital infrastructure are as follows-

  • Launch of GST- It has enabled wider availability of digitized data, which could be harnessed by lenders for credit scoring
  • Startup India- The scheme aims to provide regulatory & financial support to startups, and has led to an increase in the number of fintech players in the country.
  • Launch of IndiaStack- The unified software platform is a set of open APIs that could be utilized by banks, telecom operators as well as fintech lenders to gain insights into consumers across segments & offer them innovative lending solutions.
  • Recognizing P2P Lenders- RBI has categorized P2Ps as NBFCs, enabling growth of the segment.
  • Regulatory Sandbox- This RBI initiative allows Fintechs to test their products & innovations on a small scale & in a controlled environment before rolling them out. This allows digital lenders experiment with their innovative solutions with regulatory backing.

Reimagining Traditional Lending

Fintechs  in the digital lending space can leverage advanced technologies & regulatory provisions to  reimagine & restructure the traditional lending value chain. Specific touchpoints can be targeted to enhance customer experience & drive operational efficiency by eliminating the customer drop-off points from the traditional lending model. A seamless user experience can thus be offered by reducing turnaround times & disburse loans in seconds. Customer Experience in Lending

Using Salesforce to create Smarter, Faster & more Personalized Experience

With all these challenges and opportunities in digital lending, having a CRM system like Salesforce for loan origination, management & risk decisioning becomes a major differentiating factor. Integration of ecosystems to generate a single data set on Salesforce, can help increase decision speeds. Here are few advantages that Digital Lending platforms can leverage through Salesforce-

  1. Real Time onboarding, decisioning & approvals– Salesforce helps in integrating internal, external as well as credit bureau data to make real time decisions & operationalize risk models within minutes.
  2. Making Lending process more transparent for everyone– With a 360-degree view of customers at a glance, the entire lending process can be unified through a single platform, giving borrowers, lenders & underwriters, a transparent view of the lending process.
  3. Tailoring the right product for the right customer– Salesforce collates customer data from various sources to exactly know what customers need & when they need it.
  4. ‘Moment of Truth’ offers based on customer behavior– Integrating Salesforce with a loan decisioning solution allows a business to preapprove customers for specific offers. This ensures that it only promotes offers that are suitable for the customer and improves the application process.
  5. Understanding ‘Importance of Life events’ – Data analytics from Salesforce data can help businesses predict a customer’s need for financial services based on event or behavior triggers such as marriage, saving habits etc. & help reach out to them through personalized marketing campaigns.

Technological disruptions & availability of data has shifted the power from the lender to the consumer. New lending models which keep customer experience in the forefront can thus use Salesforce as a technology platform for digital lending. With an inevitable explosion of these customer-centric lending models, there’s no doubt that Salesforce is expected to be right at the centre of it.

Quantum Musings

The buzz of Quantum Computing is all around us for some time now. While scientists and tech companies are trying to validate Google’s claim of Quantum Supremacy, there have been endless efforts from Physicists, Material Scientists and Programmers to make quantum computing a reality. Be it IBM’s new 53 qubit quantum computer or Microsoft’s Topological Qubit, the tech industry giants are betting big on Quantum Computing and running dedicated quantum computing research departments to develop programmable quantum computers. All this in a hope to move to much more stable and less noisy quantum computers as compared to the current generation of NISQ (Noisy Intermediate Scale Quantum) processors. While the geniuses are hard at work in making practical quantum computing a reality, we at Aethereus started our own quantum computing journey using IBM Quantum Computing and Qiskit framework. Coming from a classical computing background it took some time for us to get our heads around the quantum computing concepts starting from Qubit to superposition and entanglements. After getting through the basics it was time to run some hands-on experiments on quantum computing and here’s how we went about it. IBM Quantum Computing and Qiskit – IBM Q Experience helped us to get our basics right, with the online Circuit Composer and notebooks we were able to try out the circuits and visualize the results online.  

We used IBM’s cloud based simulators and quantum processors to run our experiments and visualize the outputs. The online status of the processors with real time queue positioning and run results are great and were helpful in checking the queue and status of our runs. There are different capacity backends to choose from depending upon the capacity required for the experiments and they range from 5-16 qubits quantum processors to 32 bit QASM simulator. Qiskit to see our concepts in action. In our first attempt to create a quantum program we wanted to pick up something that was fun to implement and so we started with creating our first quantum emoticon from the community experiments. The result of the experiment was fascinating and the output image of the two overlapped emoticons was a clear visual demonstrating the quantum randomness. The quantum circuit of the experiment, its histogram plot and the final output was the below:

  • (a) – Quantum Circuit of the experiment
  • (b) – Histogram Plot of probabilities
  • (c) – Output quantum emoticon

The above image shows the output from a local quantum simulator, however the output from the online backend was much noisier. For our next experiment we thought of going ahead with a more practical application of quantum computing and decided to build a Truly Random Password Generator based on the findings in the whitepaper published by Seidenberg School of CSIS, Pace University, Pleasantville, New York. The objective of the experiment was to explore the true random nature of quantum computing an demonstrate how the randomness of qubits can be used to generate password characters that are truly random in nature. The quantum circuit of the experiment, its histogram plot and the final output was the below:  

  • (d) – Quantum Circuit of the experiment
  • (e) – Histogram Plot of probabilities
  • (f) – Output random characters

The above image (f) demonstrates the output of the program in the form of random set of 10 characters generated by the quantum program for creation of a random password. While our experiments just scratched the surface of quantum computing but the recent advancements like successful testing of qutrits and quantum entanglement of as high as 20 qubits may make practical quantum computing a reality much sooner than anticipated.

Stitching together the tech ecosystem for Customer Success: A peek into Salesforce strategy

Salesforce recently announced partnership with companies like Apple, Amazon and Microsoft. One one hand, this reflects stitching together of respective capabilities to create unified customer experience. However, it also reflects emergence of enterprise tech ecosystem with ‘frenemies’ coming together where it makes sense.

 

As the Dreamforce event kicked-off yesterday in style, 3 key partner related announcements caught my attention. In the past week, Salesforce announced deepening their relationship with tech heavyweights Apple, Amazon and Microsoft. In this piece, we will take a look at the key announcements and what it means for organizations.

1. The Apple partnership

What was announced?

  • Salesforce in partnership with Apple has come up with a new version of their Mobile App specifically for iOS. The redesigned CRM app, will leverage multiple iOS native features (like Siri and Face id) as part of the mobile App.
  • Salesforce also announced a pilot of Einstein Voice on Salesforce Mobile, allowing reps to enter notes, add tasks and update the CRM database using voice. With this, users can talk to Siri , (which in turn will work with Einstein Voice Assistant ) to add notes, add tasks and update CRM records rather than having to enter them manually.
  • “Trailhead Go” a new mobile based learning app with a customized user interface. This will enable on-the-go learning for users who use mobile screens for learning

What it means?

    Improving mobile productivity for CRM users is the next big frontier for Salesforce. A new generation of users is emerging, which uses mobile app as the primary means to interact with Salesforce. Salesforce has tapped into some of Apple’s native features to offer users seamless connect into Salesforce Mobile App
  • For instance, users can now log into Salesforce app using Face ID
  • Mobile App takes advantage of Apple’s Handoff feature to reflect changes across devices immediately. Salesforce App now allow users to seamlessly work on the same record between iPhone and say an iPad without losing context.
  • iPhone users can now ask Siri for their next Sales meeting and all relevant information about the opportunity (complete with Einstein scoring) will be available.

For developers, the new Salesforce SDK for iOS lets them deploy iOS native apps on lightning platform. This will enable users to seamlessly connect business apps on iOS with the Salesforce platform. For users, ‘Trailhead Go’ is a great way to continue learning in a mobile first fashion

2.  The Amazon announcement

What was announced?

  • Salesforce announced that it is introducing Service Cloud Voice, their new offering integrated with Amazon Connect, to enable contact center agents deliver enhanced customer service support.
  • Salesforce will now offer Amazon Cloud Connect (which includes VOIP computer telephony & call transcription services) deeply integrated with Service Cloud, so that intelligent recommendations from call recording can be offered to service agents to identify ‘hot spots’

What it means?

  • The integration with cloud and AI first contact centers, like Amazon Connect enables Service cloud platform to address a key gap around the call center offering.
  • The ability for Salesforce to ‘read’ call recording transcripts and offer Service Reps with intelligent ‘next best action’ for voice calls is a great value proposition. This previously needed to be handled by bespoke AI based solutions, but now can be handled with Salesforce.

3.  The Microsoft announcement

What was announced?

  • Salesforce announced Microsoft Azure as its public cloud provider for their Marketing Cloud stack (currently hosted on their own data centres) to
  • Salesforce also announced that they were partnering with Microsoft around ‘Microsoft Teams’, integrating Teams with Salesforce Sales Cloud and Service Cloud

What it means?

  • The move to Azure allows Salesforce to optimize Marketing Cloud workloads as customer demand scales. This also enables Salesforce customers to expand more quickly, given Azure’s global footprint and comply with local data security, privacy and other compliances
  •  As Microsoft doubles down on ‘Teams’, the ability to integrate Salesforce notifications onto Teams and vice versa is a huge deal for global clients of both companies like Marriott and Unilever, who will be able to address Sales productivity needs for their teams and improve customer experience

The Conclusion

Overall 3 key takeaways emerge from these announcements :

  • All the tech giants are looking to design a unified end user experience by stitching together their business capabilities (Apple+Salesforce).
  • These also reiterate the fact, that the emerging tech ecosystem is spawning more frenemies, who companies compete fiercely in one segment (Think MS Dynamics vs Salesforce), but collaborate in many other areas to create digital ecosystems and enable connected experience (e.g. Teams + Sales Cloud).
  • Finally, from a cloud infrastructure perspective, Salesforce has decided to hedge it’s bets between Amazon and Microsoft to take advantage of their respective strengths around scale, local presence and ensuring compliance for it’s customers.

Such ecosystems are only going to increase in the future, not just for technology giants, but also for players of all hues (and indeed for Salesforce customers). To borrow a phrase ‘Let a thousand ecosystems bloom’

customer360

Salesforce Customer 360 Truth : What it means for Customers ?

On Day 1 of Dreamforce, the BIG announcement coming from Moscone center, centered around a new offering called Customer 360 Truth. This builds on last year’s announcement around Salesforce’s Customer 360 vision to connect multiple customer silos around Sales, Service, Marketing, Commerce and much more. With the proliferation of digital channels and multiple customer facing applications, customer data has grown manifold. However, firms often face a challenge in piecing together this information for meaningful 360 view of customer. For instance, a customer shopping with online retailer can have cross-channel interactions, that get stored in multiple sales, call center and bespoke apps, all with a different way to identify a customer and with incomplete information about the customer in each system. The requirement of Customer 360 or Single View of the customer has been on top of the list for Customer Service Executives, Marketing Managers and Sales Teams. The ability to build together a Customer 360 view has been a holy grail for many organizations.

 

What?

Salesforce’s Customer 360 Truth offering takes aim at solving these problems and make it easier to identify and build a unified customer view. Customer 360 Truth consolidates data across Salesforce apps and external systems with the same ease and delivers this consolidated data on demand to the consuming apps. All of this, while addressing privacy, data security and compliance requirements. The Customer 360 Truth offering includes the following services:

Photo by Patrick Amoy on Unsplash

 

  1. Customer 360 Data Manager: Customer 360 Data Manager consolidates the Salesforce and external systems data through a single unified Salesforce ID for each customer. This leads to a golden copy of the customer with connected information readily available through the Salesforce ID.
  2. Salesforce Identity for Customers: The same customer gets multiple identities during their lifecycle with an organization due to unconnected apps, websites and login mechanisms. This creates a complicated mesh of usernames, login IDs and emails in the systems that authenticate the customers. With Salesforce Identity for Customers a single authentication login is created that acts as the gateway to all the organizations apps.
  3. Customer 360 Audiences: Customer 360 audiences connects the customer’s journey with the organization and creates a unified profile. Customer 360 audiences tracks the customer’s interactions across different touchpoints and delivers AI powered insights around the same.
  4. Privacy and Data Governance: Helps organizations classify the data they have in their systems, label them and ensure that data is compliant with the regulations like GDPR and HIPAA.

If we look under the hood, the Customer 360 Truth offering is powered by Cloud Information Model (CIM). If you are wondering what CIM is all about then in a nutshell it is an Open Source data model standardized by Amazon Web Services, Salesforce and Genesys along with the Linux Foundation. All components of Customer 360 Truth (except Customer 360 Audiences) are GA.

So What?

So, what does that mean for organizations? Well different things for different people. For Sales & Marketing executives, Customer 360 Truth makes it easier to identify and engage with customers in a much more personalized way. The Customer 360 audiences moves beyond traditional customer data platforms and builds a unified view across known data such as emails & first party IDs and unknown data such as website visits and device IDs. For designers and developers, having a Common Information Model allows them to build apps that can operate seamlessly with other apps as they follow a common model. The CIM is enabled by MuleSoft’s open source modelling technology making it easy for applications to adopt the same.

What does it take to turn on Customer 360 Truth?

While the implementation sounds relatively straight forward, we all know how much time and resources organizations have devoted to failed data management projects. Thus, one of the critical consideration before implementation is having a solid strategy for data governance and stewardship. Post defining the data strategy, getting started with Customer 360 Truth for your organizations seems  straightforward with key functionalities pre-built by Salesforce. . For instance, Salesforce Identity comes pre-configured as part of Salesforce 360 Truth offering along with metadata for handling privacy and  compliance. Some configurations might be required as part of Customer 360 Data Manager to identify and integrate core systems. On the integration front, integration API’s come pre-built for a variety of use cases to reduce integration effort as well. However, for custom use cases, APIs will need to be built out using Mulesoft and will require integration skillsets.

In Sum

While multiple attempts have been made by organizations and technology companies in the past to provide a unified single view of the customer, the Customer 360 Truth offering from Salesforce positions itself uniquely, as it focuses on reducing the friction that customers undergo in accessing their data spread across various systems. Of course, this would still require organizations to look at their data creation and management strategies and integrations holistically. Aethereus works with clients in defining this and ensuring that Customer 360 initiative is a success. In sum, this is a great offering from Salesforce to address Customer 360 related challenges. Organizations can leverage this offering as a launchpad for all their customer facing initiatives and demonstrate ROI on their customer facing investments.

Aethereus is now recognized as a Salesforce registered Partner

Aethereus, headquartered in Pune, India announced on 23-September, that it is now recognized as a Salesforce registered partner. Vijay Gupta, co-founder and Head of Alliances,  stated “This is a unique milestone for a company, which was achieved in just 2 months of company’s formation. Aethereus is a team of Salesforce experts with deep heritage into the Salesforce ecosystem. One of our core values is developing ecosystems that help our customers. As a Salesforce registered partner, we get access to tools to help our customers realize better value from Salesforce platform.”

 

Aethereus is working closely with Salesforce to help our customers across Sales, Service and Marketing. With our design thinking led approach, we solve unique client problems and are rapidly investing in Salesforce capabilities to offer industry focused solutions to our clients. For more details, please visit sforce.co/2mJ59S3

 

About Aethereus

Aethereus is a rapidly growing Salesforce boutique focused on US, ANZ and India markets. We are a team of strategists, designers, architects, and tinkerers, aligned to ALWAYS ON customer. We bring deep industry expertise and solid Salesforce platform knowledge to provide the right advice to our clients. We focus on multi-cloud deployments, industry clouds, and rapid sprints to enable faster concept to market.

5 Cool Einstein Features to look for in Salesforce Winter ’20 Release

Salesforce Winter ’20 release is just around the corner and I’m pretty sure that like me many of you must be waiting to try out the innovative features that Salesforce will be making available to its customers.

While there is a long list of exciting new features and enhancements in the release notes, the one I’m most excited about are the upcoming Einstein features and enhancements.

Salesforce Einstein, which brings the power of AI to Salesforce, has been making CRM processes smarter for the last 3 years and this year as well it promises to raise the bar with a number of new built-in intelligence and platform features.

Here is a list of top 5 Einstein features in the upcoming release that will make our CRM systems smarter and will provide capabilities to the Einstein platform developers for building intelligent solutions:

Let us look at them one by one:

1. Bring your own NLP into Einstein Bots

The feature will expand the horizon of Einstein Bots by allowing customers to connect the Einstein Bots to their own natural language processors. This will enable Einstein Bots to handle complex NLP scenarios which cannot be handled by the Salesforce’s out-of-the-box intent sets. The capability will also enable customers to process Bot utterances in multiple languages by plugging in the custom NLP, whether you are using Microsoft Azure, IBM Watson or AWS NLP. While the out of the box Einstein Language models can deliver exceptional customer service, the addition of this feature will help customers to deliver bespoke Bot experiences through Einstein Bots.

2. Einstein Article Recommendations

Knowledgebase articles have been the best buddies for customer service agents for ages and have been helping agents resolve customer cases through documented procedures and solutions. With Winter ’20 release Salesforce has made the knowledgebase articles even better by enabling intelligent article recommendations using Einstein AI. The feature provides the ability to train the recommendation model based on the fields that are most important for the case. Once trained the Einstein Knowledge Article Recommendation lightning

3. Automated Story Set Up and Descriptive-Only Insights in Einstein Discovery

Einstein Discovery has become smarter in the new release it can now choose columns in the dataset that have the most impact on the outcome variable. Einstein Discovery not only increases the speed of the story creation but also ensures that you don’t miss out on the important columns that can help achieve the goal of the story. The Descriptive-Only Insights in Einstein Discovery further speeds up the story creation if the desired output is to just find out what happened without analyzing the dataset for predictions and improvements. The time to analyze the dataset will be reduced with this feature and it will help in faster delivery of the “What Happened” analysis.

4. Conversational Search

Conversational Search feature in this release is a step towards querying of Salesforce object data using natural language statements. Users can get to a filtered list of records by using natural language statements related to the object and the required filters in a descriptive way as compared to creation of list views or reports which take time and effort. The dynamic nature Conversational Search feature doesn’t required the user to navigate to different places in the application to get to the records they are looking for, instead they can simply type the query in the global search box and Einstein takes care of the rest.

5. Identify Biases in Einstein Discovery

Identifying biased variables and removing them from a model is a challenge that needs addressing at every stage of the model’s life cycles. Biases can make their way into a model through different known and unknown factors and can result in a model that gives results that are biased towards a particular gender, age group or ethnicity. The new Einstein Discovery feature is a great step towards identification of such biases in the model. It helps in identification of variables that may be leading to a biased prediction by providing warnings about the biases and what their impacts are along with an option to remove the bias.

Art and Science of Salesforce Sandbox Refresh Process

If you are a Salesforce developer or an admin, you know that Sandboxes are integral part of your organization’s development and deployment strategy. Sandboxes let you develop and test your applications in a controlled environment that avoids any impact to your production environment.

Especially, if you are dealing with complex development projects, having a well thought out sandbox refresh strategy becomes critical to the velocity and manageability of the implementation. It becomes all the more important when the org is complex and you have lot of custom code along with restriction around PII data compliance or test salesforce releases.

Which brings us to the question, is Sandbox refresh an art or science?  While checklists and SOP’s (aka the Science) are important to ensure that you are not wrong footed. However, expertise and judgement (aka the Art) is equally important in more complex scenarios.

In this blog, we take you through three critical considerations, which sum up the art and science of effective sandbox refresh:

  1. Understand the type of Sandboxes you are using and their refresh limits
  2. Abide by the list of Dos and Don’ts – and a lot of them!
  3. Don’t forget those post refresh activities

Let us look at them one by one:

  1. Different types of Sandboxes and their refresh limits

*Sandbox templates

Sandbox templates allow you to pick specific objects and data to copy to your Full or Partial Copy sandbox to control the size and content of each sandbox. Sandbox templates are only available for use with Full or Partial Copy sandboxes.

Selection of type of Sandbox is dependent on purpose, volume of data required and periodic refresh requirement. Based on these factors, developer and developer pro sandbox is mostly used for development, unit testing and training, partial sandbox is used for system and integration testing, Full sandboxes for data load testing, integration testing, user acceptance testing, performance and load testing, and staging purposes.

2. Do’s and Don’ts of Sandboxes Refresh

  • Do not plan sandbox refresh during Salesforce spring, summer and winter release dates and times.
  • Data masking for data copied from production to sandbox for critical and sensitive data elements (utilize relevant AppExchange product or having customized scripts/apex class for this purpose)
  • Recommendation to plan for full copy sandboxes refresh completion for a minimum of 48 hours as the timing of the refresh is dependent on the salesforce Queue and also amount of data.
  • Building Sandbox templates depending on business requirements for refreshes in case of having multiple lines of business using one salesforce org.
  • Having proper communication plan including proposed schedule/timeline and impacted audience including integration teams, development teams who might be doing any testing on your full copy or other sandboxes
  • For having time controlled or early full copy sandboxes refreshes, contact Salesforce.com premier support in advance to identify place in refresh queue in order to get a better perspective on expected timing/completion of the data copy.
  • Have a refresh calendar setup to have right sandbox refresh strategy
  • Keep a full metadata backup of the instance being refreshed in case you have not setup DevOps / continuous integration
  • Disable Salesforce to Salesforce connection if enabled
  • Do not do sandbox refreshes during regular development times. This would increase the effort of the development team.

3. Do not forget the Post Refresh activities

Create read only users for consultants/developers in production which you have to create every time after the sandbox refresh. This way after you refresh sandbox, you can easily update them in sandboxes to give them access. In absence of this, you will have to recreate these users every time which is a waste of time. As a Salesforce admin, using these tips for effective sandbox can save you (and your users) a lot of time and avoid potential heartburn. So, here’s to the yin and yang of effective Sandbox refresh strategy!

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