AI

webinar
AI, Data Lake, Data Management, Delta Lake, General

InleData Webinar– The Next Gen Delta Lake Platform to Accelerate Your Business

Data has been in the light of ever-increasing profitability for any organization or business. It can be easily said that any business having a fast and easy data analysis process will have the upper hand in making a profit for the company at a flash speed. 

 

Without the manipulation of data, it becomes next to impossible to implement a sound business strategy. However, when one has sufficient data, unprocessed and unorganized data leads to nowhere. This is why Data management is a prerequisite for overall business growth.

 

The genuine concern is that do you have sufficient knowledge before choosing a data management tool?

 

This Webinar strives to help you comprehend all the needed factors before getting started with data analytics.

 

It will also teach you some of the salient features present in InleData, which will help you manage your business effectively.

 

Get to know how InleData can ingest data from multiple sources to gain a holistic view of their business ecosystem. 

 

As your data continues to grow, you’re left to figure out how to have a unified system to store data for several types of usage scenarios, including analytical products or machine learning workloads. 

 

Through this Webinar, you’ll also understand the critical differences between Delta Lake, Data Lake, and Datawarehouse and how a Delta Lake solution simplifies your data analytics and architecture. 

 

You will understand duplicate data and how InleData DEDUP helps manage such data without losing the original.

 

Our experts will also give you an insight into the security issues a data management tool incurs and how InleData state of the art security systems handle them.

 

Join us on Feb 24, 2021, at 11 AM EST to explore the understanding of data management and why it is so valuable and unravel how to integrate it with your workforce and business.

 

inledata-webinar

 

InleData Webinar Key Takeaways:

 

  • Data Management: Opportunities, Challenges, and Strategies
  • How a Delta Lake Solution can transform your business
  • Critical Differences: Delta Lake vs. Data Lake vs. Data Warehouse
  • How to Choose the Right Solution for Your Stack
  • Introduction and Demo of InleData

 

Webinar Details: 

Title: InleData – The Next Gen Delta Lake platform to accelerate your business

Date: Feb 24, 2021

Time: 11 AM EST | 09:30 PM IST

Duration: 30 Minutes 

 

Get yourself ready to dive into the ocean of possibilities of making your business grow, prosper, and profitable. 

Please register here

Introducing-InleData
AI, Delta Lake

Introducing InleData: The New Pioneer in Data Analytics

Introducing InleData: The New Pioneer in Data Analytics 

After a hectic year that 2020 brought to us, we are all waiting for a pleasant and warm 2021. CEPTES will be one of the first to open up the much-awaited news, happy news. With the beginning of 2021, CEPTES begins InleData Solutions. InleData is basically a very advanced data analytical service that gathers raw data without any transitional loss to provide a holistic report. The process, however, may on a first glance, looks a little complicated, but in reality, it is effortless and user friendly.

 

Wherefore InleData?

InleData is powered by some of the industry benchmarking AIs and MLS. Artificial intelligence is the future cause it is much more precise with less amount to no errors. This advanced technology also helps in categorizing types of data across a diverse list. It has always been a burden for many to classify data and manage them to determine whether it is essential or not. But with InleData, this headache is omitted.

 

Features of InleData 

Moreover, it can be effortless for InleData to derive useful information from data that was once thought to be useless by many. Simplicity, cloud compatibility, adaptability, speed, and affordability are among the principal factors on which InleData has been designed. It gives the provision for you to observe reports at any time and while processing in another term, “ Live Reports. “ InleData also takes care of the front of security. Data is a beneficial and a high-risk possession for most companies and industries. InleData thus keeps privacy and security at the most initial concern. No Data will be either lost or held by InleData. The real-time monitoring and visualization system supported through multiple storages, and API endpoints shall transform the delta data load without a full scan.

 

How It Will Help You?

The main motive for CEPTES to bring up the InleData solution is providing an advanced approach towards bringing a holistic intelligence rooted in unstandardized data. This lets companies engulf into a robust Mechanism with the support for streaming, batch unification, recovery, unique DEDUP, and compaction. Icing the tip of such a wonderful cake comes to a solution that effectively solves the need for legacy systems, outdated operability, and expensive EDWs. 

To sum up, in short, InleData will make your work easy by being,

  • Very Adaptive
  • Use of AI/ML
  • Can be easily implemented on various private and public cloud platforms
  • Easy to set up
  • Easy to use and customize
  • Cost-Effective
  • Use of advanced frameworks such as Spark
  • It can be used by any enterprise that supports multi-cloud.

 

CEPTES has long been a significant source in providing some class-leading and well-regarded solutions for multiple Fortune 500 companies divided across diverse industries. It puts the notion of making some of the most complicated tasks simple to rest assured and take care of other business sectors. As a 10-year-old Salesforce partner company with 3 global offices and has more than 200 customers divided across 5 continents. CEPTES has long been providing data and files management solutions like DataArchiva, DataConnectiva, XfilesPro, and Databakup to the business of any size and type, which has granted a peaceful place among customers badging it an honorary status-quo. 

AI, Einstein, Service Cloud

Salesforce added new Einstein AI capabilities & Quip in the Service Cloud

Salesforce has announced that they are going to introduce new artificial intelligence and productivity solutions to empower customer service agents through Service Cloud. The newly added features will help service agents to focus more on delivering the human side of service including intelligence, critical thinking and problem-solving. As delivering excellent customer service is rapidly influencing businesses, the role of service agents is quickly shifting. With the new AI-powered recommendations, automated routing, and embedded productivity and collaboration capabilities, Salesforce is transforming customer service teams to meet today’s customer service needs.

Service agent’s role is growing with AI adoption

With Einstein AI, service agents are rapidly shifting their focus from a case-centric approach to a customer-centric approach. The new AI solutions are helping service agents answer queries, and partially automating various processes. As per the third edition of the Salesforce State of Service report, 82% of the service leaders believe their customer service function must transform in order to stay competitive, and 77% of the service based organizations are planning to invest significantly in service agent training. This will impact a service agent’s role, as 71% of service agents believe their jobs are more strategic than two years ago and 75% saying their organizations are now considering them as brand ambassadors as they are on the front lines of all customer interactions.

New Einstein AI additions;

Over the years, Salesforce kept on adding new Einstein capabilities into their Service Cloud. Einstein Bots and Einstein Case Classifications were the last additions. Recently Salesforce has added four new capabilities;

  • Einstein Reply Recommendations

Einstein will include natural language processing to instantly suggest the best responses to service agents over the chat and messaging. This will save significant time and enhance the quality of the responses to customer requests.

  • Einstein Article Recommendations

Einstein Article Recommendations will automatically recommend the best knowledge articles to service agents, empowering them with the right information they need while resolving customer cases quickly.

  • Einstein Next Best Action

This will embrace business rules and predictive intelligence to suggest the next action a service agent should take while interacting with a customer. This will enhance customer satisfaction and will initiate up-selling and cross-selling opportunities.

  • Einstein Case Routing

This feature will completely automate the case routing process with machine learning that filters cases and sends it to the right queue or agent based on their skills and abilities based on their past expertise.

Empowering Collaboration: Quip for Service Cloud

The other important announcement from Salesforce was the availability of Quip on Service Cloud. Previously, service agents were spending more time in searching answers for customer queries by going through huge documentation, checking with other teams, switching multiple applications etc. This took out their focus from customer engagement. With the introduction of Quip for Service, service agents can access the collaboration tool to create, update and collaborate documents across their organization. This will definitely enhance customer service standards and enrich the customer experience.

Quip for Service allows agents to co-author documents, and help them resolve complex customer problems. This will also have live collaborative conversations directly within the case record. Admins can create and publish Quip templates in the agent console, as well as customize them based on various use cases and needs.

Salesforce bought Quip in 2016 for $750 million and till date Quip was a standalone product. Salesforce also said that they have embedded Quip in their Sales Cloud.

What does this mean for Salesforce Service Cloud users?

These newly added features will fundamentally change how various service agents are currently working. Salesforce is rapidly including Einstein AI in its portfolio. The latest additions in the Service Cloud will enable service agents to transform their roles and focus more on customer deliverables such as higher engagements and customer satisfaction. Quip for Service will allow service agents in easy collaboration and will become a viable alternative to various office automation tools. This will surely reduce huge office tool license costs.

 

CEPTES offers Salesforce Service Cloud Solutions

CEPTES offers end-to-end Salesforce Service Cloud solutions ranging from implementation, consulting, migration, support, and enhancement. Our Salesforce certified Service Cloud consultants are experts in optimizing customer support processes and we are one of the pioneers in offering Salesforce Service Cloud implementation services to business of every size and nature. We can help your service agents close deals faster, offer intelligent self-service, personalize customer care and predict needs, and drive service productivity from the call center to the field. Get in touch with our Service Cloud experts today!

AI, Salesforce

Salesforce acquires Marketing Intelligence firm Datorama to accelerate it’s AI investments

World’s no.1 CRM provider, Salesforce has acquired Israeli marketing intelligence firm Datorama to accelerate its AI initiatives. Though the financial terms of the deal were not disclosed, but few reports indicate that the deal is worth more than $800 million.

Salesforce has been a key player in the world of digital transformation which is transforming companies to move their business to the cloud platform in order to bring more scalability.

Datorama’s cloud-based AI platform has been used by many marketers to connect and draw business insights from data that can be used to optimize workflows and offer more personalized customer services. Currently, Datorama has more than 3,000 global customers and employs over 400 people. They previously raised $50 million in private money.

Salesforce aims to use this acquisition to reinforce its own data analytics inclinations within its Marketing Cloud. Datorama’s platform will support and integrate with Google Analytics 360 and Salesforce’s Marketing Cloud Einstein to take Salesforce’s AI initiatives to the next level.

Datorama CEO and co-founder Ran Sarig said in a blog that; “This deal will enable their company to move with higher rate while increasing data intelligence for Salesforce customers. Salesforce’s acquisition of Datorama will enhance Salesforce’s Marketing Cloud with expanded data integration, intelligence, and analytics, enabling marketers to unlock insights across Salesforce data and the myriad of technologies used in today’s marketing and consumer engagement ecosystem,” Sarig added.

Earlier this year, Salesforce has acquired Mulesoft & Cloudcraze in March. Datorama’s deal will be their third biggest acquisition of this year. Adding to this, they also integrated Google Analytics 360 & their Einstein service. This suggests Salesforce’s plan to strengthen their AI platform.

 

Source: Salesforce

AI, Salesforce

How Salesforce is using AI across its platform

In an interview during Salesforce World Tour in London this month, the head of the Salesforce Einstein product team discussed how they are using top-notch data science techniques and enable their customers to get best experiences in Salesforce’s SaaS platform.

Since Salesforce has acquired MetaMind and appointed its Founder Richard Socher as the Chief Scientist of the company, the primary objective is to implement intelligent features more into Salesforce’s CRM software. This will provide more access and insights to Salesforce’s customers in the sales, marketing, and customer service domain.

This was the idea behind the Einstein brand which was announced during Dreamforce 2016. Since then, each year Salesforce is introducing innovative groundbreaking features in it’s AI platform. Salesforce’s AI and Machine learning in-charge Marco Casalaine and his team work with all the product teams on each cloud platform within Salesforce – be it Marketing, Sales, Service, Analytics or Commerce, to discover areas where AI could be used to make it better. Salesforce has embraced AI in various platforms as well as in MyEinstein platform, which presents the underlying technology to customers looking for customized deployments.

Customized AI with MyEinstein
MyEinstein represents Salesforce Einstein, which is AI for it’s CRM platform. The objective is to allow customers to develop custom AI models on their Salesforce data to help them predict business outcome and take productive business decisions.

Enterprises can develop smarter, more predictive applications which can leverage their Salesforce data and solve their specific business challenges with MyEinstein. So, without the need for a data scientist, an organization can have AI that is customizable for their business.

Einstein Vision
Now you can harness the power of image recognition to resolve a broad range of specialized use cases by leveraging pre-trained classifiers.

Einstein Object Detection
Train models to identify objects within the images and detect types and numbers of the objects at scale.

Einstein Sentiment
You can now leverage the power of natural language processing to analyze the sentiment of text and classify it as positive, negative, or neutral.

Einstein Intent
Use this fully customizable service to classify the underlying intent in a body of text to understand what customers need across all channels.

Future Roadmap
Customers are expecting a lot from Salesforce AI. AI implementations take longer to roll out than usual features. Currently, Salesforce is working on Einstein prediction builder, which is built on the MyEinstein platform and is aimed at putting predictions right where you are in Salesforce.

einstein prediction builder
AI, Salesforce

Salesforce unveils ‘my’ versions of its all the AI-based platform tools

Salesforce Einstein, the artificial intelligence is now embedded within the Salesforce platform, hence making Salesforce world’s smartest CRM solution.

The Salesforce Einstein delivers advanced AI capabilities into sectors like: Sales, Marketing, Service and so on. It therefore, empowers companies to deliver some of the most personalized and predictive customer experience. It as well enables everyone to build AI-powered apps.

There have been various new capabilities, that allows the non-technical users to build their own predictions, customer service bots and even gamified learning courses. Salesforce, is also looking forward to making its platform more customizable with the announcements of certain new tools – with “my” prefix.

Almost a year ago, VP of Einstein Marketing Jim Sinai, indeed pointed out in a phone briefing, that Salesforce has announced its Einstein layer of artificial intelligence across its marketing, sales, customer service and other cloud sectors. During that year he also emphasized on delivering AI for applications.

Sinai as recently announced that Einstein is getting a new set of job descriptions – at the same time providing support for new tools, which allows users to customize AI based capabilities. In this genre the new myEinstein AI platform services let the users point and click their way towards custom applications with some new tools like; Prediction Builder and Einstein Bots.

It has been quoted by Salesforce, that its clouds generate almost half a billion predictions daily. In fact, the Prediction Builder allows any non-technical user to simply tap into that forecasting fall, through an on-screen wizard that guides users to create models for structured and un-structed data. It is also stated that these predictions can be employed to envision business outcomes, such as the likelihood which a given business account can cancel, based on all such data like; nature of account’s customer service calls or even at times the purchase history. Once the prediction is created it can be simply embedded into the account page, so that later, it can alert the representatives to high risk customers.

On the other hand, the Einstein Bots offers similar kind of DIY ability for the users of Salesforce’s Service Cloud. Again, through the help of point-and-click a user can create bot for answering questions or even retrieving information from customers.

The natural language processing interprets customers’ text communications, and also the Bot can be trained with much data from previous customer service encounters or from customer relationship management (CRM) records to handle all such routine matters as even tracking order status, even resetting a lost password or even begging the process of returning a purchase. The bot is designed in such a way that it will automatically handoff to humans if the communication becomes too complex, and agents, customers can provide feedback to help improve the Bot.

The bots can also be enhanced by developers with all the existing Einstein Language as well as the Vision capabilities; such as training the bot to recognize sentiment or to even visually recognize products in images.

In the year 2014, Salesforce also introduced a free learning gamified platform, more commonly known as TrailHead; that has been designed to mainly help customers learn about the platform. Now the newly introduced platform is known as ‘myTrailhead’, so that the Salesforce customers can create and even brand their own learning content.

The new myTrailHead includes various aspects like TrailMaker to create custom content for all such purposes as training customer service agent with best practices or even onboarding new hires. There is also TrailMixer, that allows the sharing of learning paths, so that all the top managers could create one and then the line managers could modify it for their purpose.

Trail trackers offers gamified leaderboards, where the badges can be awarded to everyone who completes a course. And also Trail Checker let companies build challenges and award badges to test specific skills.

Lightning in Salesforce’s component-based framework for building custom applications, and also the new myLightning lets companies create the customized, branded applications. A company can also design the workflow, as well as allow different components to appear for various scenarios. myIOT, Quip, is also the new tool for enterprise users that Salesforce hopes will tackle most of the central problem for the IoT (Internet of Things), which is the abandonment of many projects because collecting data from so many data sources is too much complex.

With the introduction of myIoT, all the non-technical users can always point-and-click their way by simply collecting and combining data from various supply of sources, even via rules-based automation. Salesforce even gave examples of automated workflows from dealerships that scheduled service calls when ever car issue data showing that they have reached a particular mileage.

However, we are yet to discuss about the new one; mySalesforce, that lets users build an application with the point-and-click tools employing the Salesforce Lightning App Builder. The app can always have a company branding, along with new listing wizard that can automatically test, configure and also publish the app to either Apple’s App Store or Google Play.

Hence, it can be considered that this new version of AI based platform can work wonders for all organizations and help them activate the business goals more easily.

fourth-industrial-revolution
AI, Dreamforce

Fourth Industrial Revolution – Few Points to Pick at the Forum

It’s quite amazing to acknowledge how ‘Fourth Industrial Revolution’ is indeed shaping up the world around us and at the same time creating a huge impact. Today let us discuss how to harness the power of this revolution and its impact over everyone.

Are you interested in a specific new technology, for instance AI (Artificial Intelligence)?
Then this year’s biggest cloud event can be one of the hub for you. To acknowledge the actual role of business in this rapidly changing world and to understand how can we work collectively to ensure that technology is a force for good.

This year at the biggest cloud event, is hosting an event of partnering with World Economic Forum, the International Organization for Public-Private Cooperation, to explore all the key challenges of achieving highest ROI, drive the positive changes, and also improve the state of the business affairs. In this promise the relationship between individual and institutions is as well explored, along with the opportunity to explore AI in a way that promotes business functionality.

The event is everything about how to change the concept of business in society and as well as how the leaders can respond to the rapidly changing market trends. The forum will also grab some of the best ideas from the well-known speakers. The forum will also examine the results of the World Economic Forum’s forthcoming Global Gender Gap Report – that simply measures the parity between men and women, along with considering all the actionable insights from various leaders to close the gender gap.

Hence, it can be concluded that this entire event is all the recent market trends and have the best of collection for the business data. In fact, is the sole platform where you will get a detailed conversation over technology as a force for social good. So, go ahead, pack your bags and get ready for the biggest cloud event of 2017, and all its discover all its branches. It’s time for some revolution in the industry.

The-5-Trends-of-IT-to-Watch
AI, IOT, Trending

The 5 Trends of IT to Watch

Where is IT heading in future? 

Some of the experts point to five trending aspects that will impact IT industry within the recent years. Both business and the workplace this year will be affected. Together, the trends point to a further acceleration of the entire digital transformation and the widening gulf between traditional and the digital innovation.

The Expansion of IoT – Internet of Things

The IoT is mainly the concept of connecting almost every device with the Internet. These things can be as small, as phone or even a coffee maker, while it can also be as large, as an autonomous vehicle. This concept is indeed applied to the home, the workplace, transportation networks, hence, blurring the lines between the digital and physical lines. It also has a huge impact on all aspects of life.

The basic definition for IoT is that it will redefine our relationship with objects and the relationships of all the internet-connected objects to each other.

The Connected Digital Mesh

The digital mesh is said to be comprised of people, some smart machines, the internet-connected devices, content and the services. The expanding and all the interoperable set of endpoints people can utilize to access applications and information, or even interact with other individuals, self-selected communities and businesses.

The Challenge of Security

There have been many expansions in digital technology, like the IoT and the Digital Mesh will require some multi-layered security that can indeed adapt via the behavioural analytics. As these technologies extend to every workplace, the need for adaptive security will become universal.

It has been seen that all types of risk, from regulatory compliance to natural disasters will be developed and adopted.

The Promise and Possibilities of AI

There are some well-funded startups that continue to pursue AI: the intelligent systems that can learn independently, adapt and as well extend to every technology-enabled service, object or application. Still, there is some dispute about how “intelligent” AI is at the current juncture because it has been performing based on preset instructions.

The Adoption of various IT Techniques in Start-Up

Development techniques that are very common in the tech start-up environments will indeed increasingly be adopted to the reinvent established IT workplaces because they actually deliver competitive advantages.

Open source software, the Agile practices and as well as the DevOps have long been used in start-ups in order to bring faster time to market, lower development cost, acute collaboration opportunities, and much more faster adoption by users.

These agile practices rely on incremental, iterative work cadences as one of the alternatives to traditional project management and sequential development, hence, increasing productivity.

impact-of-ai-appllication
AI, Finance & Accounting

Machine Learning in Finance Industry The Impact of AI Application – CEPTES Study

Machine learning have proved to be one of the fruitful applications in finance industry. In fact, this has effected the entire genre, even before the advent of mobile banking apps, or the proficient chat bots.  Owing to the high volume, accurate historical records, and as well as the quantitative nature of the finance world, it is better suited for artificial intelligence.

It has been estimated that today, machine learning has come to play, in an integral role in the various phases of the financial ecosystem. Its wings are spread across the genre like; approving loans, to even managing assets.

Today we will explore both the current and future applications of artificial intelligence in finance. It is also intended as an executive overview rather than just being a granular look at all applications in this genre.

The Role of Machine Learning in Finance Industry 
Current Applications

Let us have a look at some of the examples of machine learning being put to use actively today.

The Portfolio Management

The very famous term robo-advisor, was essentially unheard, just five years ago, but it now holds a commonplace in the financial landscape. The term is also misleading and does not involve robots at all. Rather, the term is related to algorithms, built to calibrate the financial portfolio to the goals and also to the risk tolerance of the user.

The system is said to calibrates to changes in the user’s goals and as well to the real-time changes in the market, aiming always to find the best suited solution for the user’s original goals. These also have gained significant traction over human advisors.

The Algorithmic Trading

Going back to the 1970’s, the algorithmic trading, sometimes also called “Automated Trading Systems,” used to involve the use of complex AI systems. This was done to make extremely fast trading decisions. These algorithmic systems helped in making thousands or millions of trades per day, hence, they were given the special term “High-Frequency Trading” (HFT).

Most of the hedge funds and as well as the financial institutions do not openly disclose any of their AI approaches to trading (for good reason), but it has been believed that machine learning and the process of deep learning are playing an integral role in calibrating trading decisions in the real time.

The Fraud Detection

The process of combining more accessible computing power, internet is becoming more and more common. Along with this there has also been an increase in the amount of valuable company data being stored online, and then you have a “perfect storm” for the data security risk.

While the previous financial fraud detection systems were majorly depended on the complex and robust sets of rules, the modern fraud detection goes beyond. This is the one that actively learns and calibrates to all the new potential (or real) security threats. This is hence, the place of machine learning in finance for fraud.