by Teknita Team | Jul 1, 2022 | Uncategorized
Microsoft is introducing Viva Sales, a new seller experience application that brings together any customer relationship management technology (CRM), Microsoft 365 and Teams to provide a more streamlined and AI-powered selling experience.
Viva Sales is a new modern way of selling. As a smart CRM companion, Viva Sales makes sellers’ lives easier while enriching their CRM. Think about all the customer and deal insights that are already in Outlook, Teams and Office applications like Word, Excel and PowerPoint, but never make it into the CRM system. These insights are hard to capture because the seller is tasked with entering data manually. By enhancing the CRM system with customer engagement data from Microsoft 365 and Teams along with the power of artificial intelligence (AI), Viva Sales empowers sellers to be more connected with their customers, resulting in more personalized customer engagements and closed deals faster. This happens through a simple customer tagging feature, which automates the data capture, saves the seller time, and provides their organization with a more complete picture of deal and customer status. With AI embedded throughout, Viva Sales is like a sales coach to move deals along with recommendations and reminders. This intelligence layer provides sellers the information they need to help them be more productive.
You can read more about the Viva Sales here.
You need more details?
For a complete list of new features and fixed issues, or to discuss any particular use case for your business applications, please contact us.
by Teknita Team | Jun 30, 2022 | Content Services
Microsoft is excited to announce the Data Hub!
The Data hub is the evolution of the Datasets Hub that was announced in December-2020.
In the Data hub, in addition to Power BI datasets, users can now find the newly released Datamarts.
The Data hub is a central location for data owners, report creators, and report consumers to manage, discover and reuse data items across all workspaces.
- Data item owners can see usage metrics, refresh status, related reports, lineage, and impact analysis to help monitor and manage their data items.
- Report creators can use the hub to find suitable items to build their reports on and use links to easily create the reports.
- Report consumers can use the hub to find reports based on trustworthy data items.
A major challenge for customers is that users often build similar data repeatedly, resulting in resource overload, governance complexity, and difficulty in identifying sources of truth.
The Data hub addresses these challenges by making it easier for users to discover existing, quality data and reuse it to answer business questions and gain insights.
Once user discovers a data item that seems to have the right data, a click on the item opens the data details page. On the details page you can see the following:
- Metadata about the data item, including description, endorsement, and sensitivity label.
- Actions such as share, refresh, create new, and more.
- Related reports, which are reports that were built on top of the dataset/datamart.
Data discovery best practices – before creating new reports, users should look at the existing related reports. If there are no such reports that are suitable, there are multiple ways to create a new report:
- Create report from template, if a template has been defined (a template is defined by adding the suffix “(template)” to a report built on top of the dataset/datamart).
- Create report from scratch to open a blank canvas and start creating your report.
- Auto-create a report. Note: This is currently supported only for single-table datasets.
- Create a formatted table.
You can read more about the Data hub here.
You need more details?
For a complete list of new features and fixed issues, or to discuss any particular use case for your business applications, please contact us.
by Teknita Team | Jun 29, 2022 | Uncategorized
CockroachDB 22.1 helps you to build better with less effort, at every stage of your application lifecycle. CockroachDB was made to enable use the same database from start to scale, without rebuilding an app and without crippling, complex operations.
CockroachDB 22.1 enables engineering teams to:
Developers can stand up CockroachDB and integrate it with their stack quicker than ever with:
– A new command-line tool (CLI) so users can manage and scale their cluster with code
– Integrations with the popular tools Prisma and Google Pub/Sub
– Support for time-to-live (TTL), which lets developers set a lifespan for row-level data
– Improvements to the developer-first offering, CockroachDB Serverless
- Optimize more efficiently & avoid toil.
CockroachDB already eliminates common database pains like downtime for maintenance, frequent patches, or black boxes around performance. With CockroachDB 22.1, users can now:
– Automate deployment and scaling with a new administrative API
– Optimize performance more easily with index recommendations and insights into transaction contention
– Monitor their clusters with a new integration with Datadog
- Scale better to meet peak demand, everywhere.
CockroachDB already automates and simplifies scale. This release adds updates including:
– Quality of Service (QoS) to let users maintain peak performance while handling millions of transactions per second
– A new capability to address data domiciling regulations for multi-regional and multi-national businesses
You can read more about CockroachDB 22.1 here.
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by Teknita Team | Jun 28, 2022 | Artificial Intelligence - Machine Learning
Retailers, along with used product resellers, non-profits, thrifters and liquidators, want to capitalize on this thriving reCommerce market to cut the billions of dollars going to waste. AI and machine learning has become the answer. Here are the key ways AI is enabling the reCommerce industry to scale.
- Attribute Identification.
Using AI and machine vision, resellers are able to quickly take what was once a very manual process of identifying and assigning product attributes and automate this identification process. Product characteristics such as color, style and even brand can be quickly assessed, automatically, using simple photographs. This can cut hundreds of hours off product processing when used for large batches of items, such as returns, donations and overstocks.
- Product Valuation.
Returned, donated and used items typically don’t have designated tags or SKUs that can identify the value or assign a price. Using AI technology, identified attributes can be used to scour data sets across resale markets to properly identify current item value and set a market price. This too takes hours off of the traditionally manual product pricing process and is very effective at optimizing resale revenue.
- Marketplace Listing Automation.
Product marketplaces from Poshmark, threadUP and The RealReal to eBay, OfferUp and Facebook Marketplace all require specific adjustments and characterizations to effectively list on their sites. AI technology and automation is being used to produce fully compliant, SEO optimized listings for each marketplace so that products are showcased effectively, no matter where they are being sold.
- Empowering Listing Volume.
Listing products for resale is a numbers game. And with so much product volume to move, retailers specifically need to optimize their listing abilities to recoup lost profits from returned goods. AI empowers scalability and incredible volume, enabling sellers to move from a 5,000-item turn a month to exponentially increase overnight.
- Lowers Labor Costs.
The cost of human labor has been the number one barrier to increasing reCommerce scale. Through AI and machine vision technology, resellers are closing the labor gap and optimizing profitability without the costs, challenge and difficulty of recruiting workers or shipping product offshore to perform processing. This further reduces costs and enhances rapid growth through product processing scale.
You can read more about Ways AI Is Powering ReCommerce here.
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by Teknita Team | Jun 27, 2022 | Security
Cookies refer to one or more small pieces of data that identify your computer to a website with a unique code. The cookies are sent by a web server to your device while you’re on that server’s website. Your computer stores that cookie and, when you visit that website again, the server can recognize that the device is the same one as was used previously.
Cookies are generally broken into two groups:
- Session cookies, which expire immediately after you’re done being online
- Persistent cookies, which stick with you during many different web sessions
Cookies can be extremely useful. For example, authentication cookies, allow a user who logs into a website to click and view multiple pages on the site without having to re-authenticate each time he or she tries to access another page requiring authentication. Cookies can also allow a site to remember a user’s username without authenticating the user, or other personalization preferences.
Cookies are heavily utilized by marketing firms who can target your interests and buying habits. Cookies are the reason why you might be eyeing a new pair of sandals on one website and then see ads for that same pair of sandals when you’re on other websites. That proves cookies aren’t always great. Privacy issues are one thing to consider. Many sites now use third-party cookies. Many sites, for example, may present banner ads from the same ad provider, and the code from that provider can send and receive cookies to run on all of those sites, enabling it to track your activity across multiple sites. According cybersecurity specialists, it is best to know who is following your activities, and you should review and clean out cookies that may be unwanted.
You can read more about cookies and how to delete them here.
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