Why Adaptive AI Can Overtake Traditional AI

Why Adaptive AI Can Overtake Traditional AI
With the ever-changing technology world, company demands and results are no longer the norm. Businesses in a variety of sectors are using artificial intelligence (AI) technologies to solve complicated business challenges, build intelligent and self-sustaining solutions, and, ultimately, remain competitive at all times. To that aim, ongoing attempts are being made to reinvent AI systems in order to do more with less.

Adaptive AI is a significant step in that direction. It has the potential to outperform standard machine learning (ML) models in the near future because of its ability to enable organizations to get greater results while spending less time, effort, and resources.

The capacity of adaptive AI to enable enterprises to achieve greater outcomes while investing less time, effort, and assets is why it can overtake traditional AI models.

Why Adaptive AI Overtakes Traditional AI

Robust, Efficient and Agile
Robustness, efficiency, and agility are the three basic pillars of Adaptive AI. The ability to achieve great algorithmic accuracy is referred to as robustness. The capacity to achieve reduced resource utilization is referred to as efficiency (for example, computer, memory, and power). Agility manages the ability to change operational circumstances in response to changing demands. Together, these three Adaptive AI principles provide the groundwork for super-capable AI inference for edge devices.

Data-Informed Predictions
A single pipeline is used by the adaptive learning approach. With this method, you can use a continually advanced learning approach that maintains the framework up-to-date and encourages it to achieve high levels of performance. The Adaptive Learning method examines and learns new changes made to the information and produces values, as well as their associated attributes. Moreover, it benefits from events that can modify market behavior in real-time and, as a result, maintains its accuracy consistently. Adaptive AI recognizes information from the operational environment and uses it to produce data-informed predictions.

Closing Lines
Adaptive AI will be utilized to meet changing AI computing requirements. Operational effectiveness depends on algorithmic performance and available computer resources. Edge AI frameworks that can change their computing demands effectively reduce compute and memory requirements.

Adaptive AI is robust in CSPs' dynamic software environments, where inputs and outputs alter with each framework revamp. It can assist with network operations, marketing, customer service, IoT, security, and customer experience.

Spotlight

Careerera

Careerera is an online education provider company of professional certification training, based in Herndon, Virginia, USA. Careerera is regarded as one of the front-runners in offering qualitative online courses to the ones who really wish to go ahead in their career by earning quality certifications. All the certification courses provided by us are in complete sync with the liking and requirements of the students.

OTHER ARTICLES
Business Intelligence, Big Data Management, Data Science

Predictive Analytics: Implementation in Business Processes

Article | May 2, 2023

Knowledge is power in business, and knowing what will happen in the future is a superpower. When data analytics, statistical algorithms, AI, and machine learning are combined, this superpower, also known as predictive analytics, becomes a skill that can significantly influence on a company's choices and outcomes. Predictive analytics is the use of modern analytical tools. For example, machine learning concludes about the future based on historical data. Businesses can consider application of predictive analytics tools and models to forecast trends and generate accurate future predictions by leveraging historical and current data. Let’s look at the top three reasons why predictive analytics is important for your business. Why is Predictive Analytics Important for Businesses? Businesses are looking at predictive analytics to help them solve challenges and discover new opportunities. Here are some of the most common benefits of predictive business analytics and an understanding of how is predictive analytics used in business. Fraud Detection In general, various analyzing techniques are merged to analyze data to enhance the accuracy of pattern recognition and discover criminal behavior, thereby reducing the incidence of frequent fraud. With behavioral analytics, you can look at any suspicious behavior and activities that happen on a network in real-time to look for fraud, zero-day breaches, and underlying threats. Enhancing Business Campaigns The predictive analytics process can help you optimize marketing campaigns and promotional events. Predictive designs helps businesses attract, retain, and increase valuable customers by determining their purchase responses and promoting cross-sell opportunities. Minimizing Potential Risk The predictive analytics process helps businesses decide on appropriate steps to avoid or reduce losses. Predictive analytics is revolutionizing risk management by alerting businesses about future developments. For example, credit scores, which financial institutions use to predict defaulters depending on a user's purchasing behavior. How Does Predictive Analytics Help the C-Suite? The C-suite is the final decision maker, so they are the ones who must use predictive analytics the most for insightful decision-making. Let’s look at ways in which predictive analytics can help C-level executives. Predict Customer Behavior Predictive analytics utilizes data to forecast future customer behavior. Customer intent becomes the primary aspect rather than historical transactional data, allowing for hyper-personalized marketing and communications. For example, researchers at China's Renmin University used predictive analytics and machine learning to figure out that data on consumer interests and jobs can predict customer preferences and purchase intent for cars. Predicting customer requirements accurately is a huge opportunity for businesses. Companies can use AI and predictive analytics models to figure out what customers will do based on data instead of guesswork. Pricing Optimization Predictive business analytics can help companies improve pricing optimization quickly and affordably. A business can use predictive analytics to figure out how to make a product more affordable in the future by looking at past data, industry trends, competitive prices, and other data sources. Each customer provides a unique value to the products. To add to the complexity, a consumer's value of a product may vary depending on the purchase circumstances and environment. Simplicity in pricing misses opportunities and can result in a significant drop in revenue. Product information, consumer segmentation, and purchase circumstances are all enhanced by predictive analytics. Businesses can use this data to uncover trends and patterns to help them price more profitably. Predicting Growth and Market Trends Businesses can use predictive market analysis to decipher existing and future market trends. With this data, businesses can develop a plan to maximize opportunities, expand market share, and sustain disruption and new competition. Companies can use it to detect unmet customer demand and fill any gaps. Consumption sentiment is revealed through social media data. A product that does not match customer demand creates a market opportunity for a new product or service. Predictive market analysis can uncover customer perceptions of a product or service and unmet consumer demands. Predictive business analytics helps businesses better understand their customers, meet their needs, and find new ways to earn revenue and grow. Example: Reu La La Uses Predictive Analytics to Increase its Revenue by 10% You often hear about giant enterprises like Amazon, Airbnb, Microsoft, Google, and others utilizing predictive analytics to extend their reach, boost sales, and more. Today let’s look at Reu La La and how they used predictive analytics to enhance their revenue. Rue La La, a boutique retailer, often needs to predict sales and fix pricing for products being sold for the first time in its online store with no existing sales data. They observed that many products were either sold out within the first few hours of release or did not sell, which lead to revenue loss. Rue La La took action by creating a set of quantitative qualities for its items and predicting future demand by utilizing historical sales data. They used statistical and computing technologies, such as regression analysis and machine learning, to create a demand forecast and pricing optimization model. In partnership with the Massachusetts Institute of Technology, they created an automated price decision assistance tool. Revenue increased from 10% to 13% across all departments because they used the pricing tool's proposed optimal rates. Conclusion “As data piles up, we have ourselves a genuine gold rush. But data isn’t the gold. I repeat, data in its raw form is boring crud. The gold is what’s discovered therein.” Eric Siegel You can consider the predictions that predictive analytics makes as gold, but, using predictive analytics is like a crystal ball that shows the future. You can look into the future, prevent issues in your company from escalating, and recognize profitable possibilities. If you haven't started leveraging predictive analytics, start by experimenting with it on a modest scale and gradually build up as you acquire expertise and observe positive outcomes. FAQ How can Predictive Analytics Improve Performance Measurement? Predictive analytics improves performance measurements by expanding an organization's understanding of the important performance drivers. It also helps with the weighting of different performance metrics based on how important they are. What Are the Four Steps in Predictive Analytics? In simple terms, predictive analytics involves four steps: creating a baseline prediction, assessing it, adding assumptions, and building a consensus demand plan. To do so, we must first choose a modeling technique, create a test design, then construct the model, evaluate the mode, and achieve alignment. What Are the Three Different Types of Predictive Analytics? Businesses utilize three forms of analytics to drive their decision-making: Descriptive analytics — tells something that has already happened; Predictive analytics — shows what can happen; Prescriptive analytics — tells what should happen in the future

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Business Intelligence, Big Data Management, Big Data

Data Visualization: Why Does It Matter in Businesses?

Article | July 4, 2023

Data visualization refers to a graphical representation of information that displays patterns and trends while allowing viewers to gain rapid insights. Data visualization is critical for businesses to quickly detect trends in data that would otherwise be time-consuming. However, making sense of the quintillion bytes of daily data is difficult without data proliferation, including data visualization. Understanding data is beneficial to every professional business; hence, data visualization is spreading to all fields where data exists. For any company, data is its most valuable asset. One can effectively communicate their points and use that knowledge by using visualization. "Data visualization is a great way to simplify data and show it in a form that is understandable, insightful, and actionable. Data visualization is being increasingly seen as the vital final step of any successful data-driven analytics plan." Caroline Lee, CocoSign Why Does Data Visualization Matter? As we acquire more and more data, data visualization becomes increasingly critical, to the point where we are nearly drowning in information, and it is difficult to distinguish what is significant and what is not—for example, the product development program for a new automobile or plane. Analyzing test data is vital, but a massive amount of information is created with each test drive or flight, making processing at the required speed challenging. Visualization tools help comprehend complex data and detect patterns and anomalies. Visual information accounts for 90% of the information sent to the brain. Data visualizations can shorten business meetings by 24%. Managers who use visual data recovery tools are 28 percent more likely than those who rely on managed reporting and dashboards to find timely information. 48% of these managers can find the data they need without the help of I.T. staff. For every dollar spent on business intelligence with data visualization skills, $13.01 will be returned. Let us look into some of the benefits of data visualization in businesses. The Creditable Impact of Data Visualizations on Business While big data is ruling industries, business intelligence transforms much of this data into actionable data points. As a result, data visualization plays a role in transferring information to the human brain by swiftly presenting data. Visualization has a lot of aesthetic importance in representing and conveying a clear message. Businesses that rely solely on data will eventually go out of business if data visualization is not implemented. Data visualization's competitive benefits can make or kill enterprises. It is critical to know that there are no shortcuts to making faster and better judgments without visualizing the data. Data Visualization Helps You Take Better Decisions Based on Data Unlike meetings that focus on text or numbers, business meetings that address visual data tend to be shorter and easier to reach consensus on. Data visualization speeds up decision-making and allows viewers to better understand patterns and trends. The benefits of data analytics can be accessed across all departments, right from admin to IT, sales to marketing. Even if they are not experts at reading data, your sales team can better understand consumer behavior and impressions if the correct data visualization solutions are in place. With the proper training and tools in place, you can build specialists using data visualization, a combination of technical analytics, and artistic narrative. When visualizations are created to meet your business goals, you will obtain the best results. For example, some data visualizations help in analysis, while others make the data visually appealing. Some are created to demonstrate concepts, processes, or tactics to various audiences. You can create your own based on your specific goals, data types, and stakeholder requirements. Data Visualization Is a Medium to Tell a Data Story to the Viewers Data visualization can also tell a story about data to the audience. The visualization can convey facts in an easy-to-understand format while creating an account and bringing the audience to a predetermined conclusion. This data tale should have a strong start, a basic storyline, and a logical decision like any other story. If a data analyst is tasked with creating a data visualization for company leaders that details the profitability of various items, the data story could begin with the profits and losses of multiple products before moving on to advice on how to address the failures. Create your own depending on your specific goals, data types, and stakeholder requirements. Data Visualization Helps You Gather Data Faster and Saves Time Data visualization is a much faster way to get insights from data than examining a chart. Using data visualization, business meetings can take decisions faster, saving time. When the long meetings are cut short by utilizing data visualization, businesses can dedicate more time to other core business activities. Summing up To develop excellent data visualizations, various tools and methodologies are available. You and your team must comprehend the fundamental principles and choose appropriate tools. Above all, the data must be presented accurately. Layouts, colors, text, and dashboards must be appropriately crafted to build data visualizations that best help your business objectives. Frequently Asked Questions Why is data visualization important? Presenting data in a visual or graphical style is known as data visualization. It allows decision-makers to see analytics in a graphic format, making it easier to grasp complex topics or spot new patterns. What are some of the types of data visualization? There are several types of data visualization. They are line graphs, scatter plots, pie charts, heat maps, area charts, histograms, and choropleths. What are the main goals of data visualization? The main goals of data visualization are to understand your audience, stick to a strict timeline, and deliver a compelling story.

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Business Intelligence, Big Data Management, Big Data

A Modern Application Must Have: Multi-cloud Database

Article | July 10, 2023

To function well, modern apps require enormous amounts of diverse data from sensors, processes, interactions, etc. However, these apps cannot understand the unstructured big data and extract commercial value for effective operations unless this data is maintained properly. In today's age of cloud computing, apps gather and analyze data from various sources, but the data isn't always kept in the same database or format. While increasing overall complexity, several formats make it more difficult for apps to retain and use various data. Multi-model databases, a cutting-edge management system, provide a sophisticated approach to handling varied and unstructured data. A multi-model database allows various data models to natively utilize a single, integrated backend, as opposed to combining different database models. Why Has Multi-Model Database Become a Necessity for Modern Applications? Modern applications can store diverse data in a single repository owing to the flexible approach to database management, which improves agility and reduces data redundancy. Improve Reliability Each database might be a single point of failure for a larger system or application. Multi-model databases reduce failure points, enhancing data dependability and recovery time. Such recovery minimizes expenses and maintains customer engagement and application experience. Simplify Data Management Fragmented database systems benefit contemporary applications but complicate development and operations. Multi-model databases provide a single backend that maintains data integrity and fault tolerance, eliminating the need for different database systems, software licenses, developers, and administrators. Improve Fault Tolerance Modern apps must be fault-tolerant and respond promptly to failures promptly. Multi-model databases enable this by integrating several systems into a single backend. The integration provides system-wide failure tolerance. Closing Lines As applications get more complicated, so do their database requirements. However, connecting many databases and preserving consistency between data gathered from various sources is a time-consuming and expensive undertaking. Fortunately, multi-model databases provide an excellent option for generating the data models you want on a single backend.

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Location Intelligence

Exploring Business Success with Location Intelligence

Article | June 17, 2024

Discover the essentials of location intelligence across various industries, foundational concepts, industry-specific implementations, and location intelligence software in this insightful article. Contents 1. Introduction 2. Foundational Elements of Location Intelligence 3. Location Intelligence in Industry Verticals 4. Top Providers in Location Intelligence 4.1 Tango Analytics 4.2 Precisely 4.3 Local Logic 4.4 GBG 4.5 Nextbillion.ai 4.6 GeoComply 4.7 Mapbox 4.8 GapMaps 4.9 Qlik 4.10 Connectbase 5. Wrap Up 1. Introduction In the modern digital age, businesses continually pursue innovative strategies to gain a competitive edge and succeed. Among these strategies, location intelligence has emerged as a potent tool for driving informed decision-making. By leveraging geospatial data and advanced analytics, companies can extract actionable insights into customer behavior, market dynamics, and operational efficiencies. This article provides an overview of location intelligence, highlighting its role in enabling businesses across diverse industry verticals to navigate complex arenas and make data-driven decisions effectively. 2. Foundational Elements of Location Intelligence Geospatial Data: Geospatial data encompasses information tied to specific geographic locations on Earth's surface. It includes various types, such as vector data (points, lines, polygons), raster data (imagery), and attribute data (descriptive information about spatial features). Sources of geospatial data range from satellite imagery, aerial photography, GPS data, and LiDAR scans to census data, social media check-ins, and IoT devices. Mapping and Visualization Techniques: Mapping and visualization techniques are essential for conveying spatial information effectively. Cartography principles help design clear, informative, and aesthetically pleasing maps. Visualization techniques range from simple thematic maps to complex interactive web maps and 3D visualizations. GIS (Geographic Information Systems): GIS software allows users to capture, store, analyze, and visualize geospatial data. It enables the integration of various data types and provides tools for spatial analysis, such as overlay, proximity analysis, and spatial querying. In addition, Geographic Information Systems software is crucial in creating and analyzing spatial data. GPS (Global Positioning System): GPS technology provides precise location information by utilizing a network of satellites. It is widely used in navigation, asset tracking, surveying, and location-based services. Remote Sensing: Remote sensing involves capturing information about Earth's surface from a distance, typically using satellites or aircraft. It provides valuable data for monitoring environmental changes, agriculture, disaster management, and natural resource management. 3. Location Intelligence in Industry Verticals Location intelligence finds applications across various industry verticals, each with its unique challenges and opportunities. Transport and logistics organizations leverage location intelligence software to optimize supply chains and streamline delivery operations. With location analytics, fleet managers can minimize delivery time and control warehouse loading and unloading processes. Real-time monitoring helps in route accuracy, identifying delivery delays, and accurately calculating expenses, including fuel reimbursement and fleet operating costs. Location analytics is a game-changer in the pharmaceutical industry, revolutionizing on-field activities such as dispatching medicines, inventory management, and managing client visits. Companies harness location data to fine-tune sales operations and align sales territories effectively. By analyzing sales patterns geographically, pharma companies can optimize sales efforts, minimize travel time for medical reps, and ensure equitable distribution of tasks. In banking and insurance industries, location intelligence data is integral to channel optimization and sales operations. Banks and insurance companies leverage location data to expand their branch networks strategically and make informed decisions about acquisitions or investments. By engaging customers with relevant information based on their location, they can maintain positive relationships, develop better policies, and boost marketing strategies. The retail industry utilizes location intelligence to deliver personalized experiences and optimize supply chain management. By integrating location data with consumer and operational data, retailers gain insights into consumer behavior and preferences at the store level. This enables them to deliver consistent purchasing experiences, drive customized marketing outreach, and optimize supply chain processes for enhanced efficiency and customer satisfaction. 4. Top Providers in Location Intelligence When exploring the world of location intelligence, it becomes apparent that the source of the data driving these insights is a crucial yet often neglected aspect. Every business industry requires distinct datasets; not all providers offer the same breadth or depth. Therefore, understanding where to obtain these essential resources is paramount. Look at a list of top providers in location intelligence to ensure access to the precise data types required to propel your business forward. 4.1 Tango Analytics Tango Analytics solutions offer businesses the intelligence to develop more brilliant location strategies and make informed capital investment decisions. By integrating advanced modeling with robust data within a scalable geospatial analytics platform, Tango provides unparalleled insights that optimize location decisions, maximizing the potential for brand success. Tango's Integrated Workplace Management System (IWMS) software suite equips organizations with comprehensive tools to analyze and optimize their corporate offices or physical locations. With purpose-built GIS, predictive analytics, and management tools, Tango enables businesses to better predict and respond to market opportunities while enhancing the execution of location strategies. From space management and facilities maintenance to lease administration and capital project management, Tango's IWMS solutions streamline processes and improve resource utilization. 4.2 Precisely Precisely, a renowned leader in data integrity has expanded its portfolio with the acquisition of PlaceIQ in 2022. This strategic move has enriched Precisely’s offerings with advanced location intelligence solutions, notably PlaceIQ Audiences and PlaceIQ Movement. These solutions empower businesses to leverage real-world behaviors and foot traffic insights, enabling targeted consumer engagement and informed decision-making. PlaceIQ's platform equips businesses with powerful location-based insights, attribution, and measurement capabilities. Its sophisticated approach allows companies to understand and connect with location-based audiences, measure real-time ROI, and apply insights to drive intelligent marketing and business outcomes. Key features include implementing audience strategies with proven results, measuring foot traffic patterns for actionable insights, analyzing movement patterns for market insights, and accessing high-quality location data through subscription models. 4.3 Local Logic Local Logic specializes in providing comprehensive location intelligence solutions tailored for the real estate sector. Founded in 2015, the company emerged from a commitment to enhancing urban livability through objective data and metrics. Headquartered in Montreal, Canada, Local Logic offers tools designed to quantify and analyze location-related data, aiding residential and commercial real estate professionals in making informed decisions across the United States and Canada. Local Logic's provides comprehensive location intelligence solutions which offers granular demographic insights, proprietary location scores, detailed neighborhood profiles, real-time points of interest (POI) data, school-focused information, and climate risk assessments. These features enable users to access information crucial for evaluating property investments and matching properties with ideal lifestyles. By integrating diverse data points into intuitive tools and maps, Local Logic empowers clients to leverage data-driven decision-making in the competitive real estate market. 4.4 GBG Loqate, a GBG solution, provides comprehensive services focused on address verification, data validation, and geocoding. With a global reach, Loqate's solutions are designed to enhance data quality, improve customer experiences, and support efficient business operations across various industries. Loqate offers various critical services, including real-time address capture, address verification for 249 countries and territories, data maintenance services, geocoding capabilities, and email, phone, and bank details validation. Additionally, their points of interest and store finder feature provides comprehensive POI data to enhance location-based services. These features help businesses maintain high-quality datasets, improve operational efficiency, reduce costs, ensure compliance, and scale with business needs, ultimately enhancing customer experience and satisfaction. 4.5 Nextbillion.ai NextBillion.ai offers advanced routing and navigation solutions tailored to tackle complex logistical challenges across various industries. With an integrated platform leveraging AI-powered technology, NextBillion.ai provides a range of APIs and SDKs to optimize routing, enhance navigation, and ensure real-time tracking, ultimately improving operational efficiency and customer satisfaction. NextBillion.ai's essential products and features include the Route Optimization API, which handles over 50 constraints and customizable parameters to generate optimized routes tailored to specific business needs. The Directions and Distance Matrix API processes large matrices for accurate ETAs and distances, with scalable pricing based on fleet size or order volume. Their Navigation API & SDKs offer turn-by-turn navigation across multiple platforms. At the same time, the Live Tracking API & SDKs provide real-time monitoring and comprehensive integration with telematics and CRM systems, enhancing fleet management and operational efficiency. These features cater to various industries, including supply chain and logistics, mobility and field services, offering scalability, cost efficiency, and developer-friendly integration processes. 4.6 GeoComply GeoComply is a renowned provider of geolocation compliance and anti-fraud solutions. Established in 2011, it aims to foster a safer internet environment by combating fraud and ensuring regulatory adherence across diverse sectors such as gaming, finance, and media. GeoComply offers a suite of critical products addressing various aspects of fraud prevention and compliance. GeoComply Core provides precise geolocation data and anti-fraud solutions, which are crucial for industries like online gaming and financial services. GeoGuard, its award-winning solution, identifies and blocks fraudulent access through VPNs and proxies, safeguarding geolocation data integrity. IDComply offers comprehensive KYC & AML solutions, ensuring regulatory compliance with identity verification requirements. PinPoint provides custom geofencing solutions for on-property location compliance, while GeoComply Chargeback Integrator (GCI) automates chargeback management to combat fraud effectively. These solutions deliver enhanced security, regulatory compliance, operational efficiency, and revenue optimization benefits trusted by leading businesses worldwide. 4.7 Mapbox Mapbox is a premier provider of mapping and location data platforms, offering developers a suite of tools and services to craft bespoke maps, navigation systems, and geospatial data solutions. With a founding mission to democratize mapping and deliver highly customizable, performance-driven mapping solutions, Mapbox serves a diverse array of industries, including automotive, logistics, and mobile applications. Mapbox's key features and services encompass various offerings tailored to diverse developer needs. Mapbox Studio enables users to create and customize map styles, incorporating features like 3D buildings and terrain contours for enhanced functionality and aesthetics. Navigation solutions include SDKs for mobile and automotive applications, featuring embedded routing, turn-by-turn navigation, and specialized solutions such as Mapbox for EVs, catering to electric vehicles with route planning and battery range predictions. Location data and analytics offerings include Directions and Matrix APIs for optimal route calculation along with real-time data integration for accurate, up-to-date maps and traffic information. Cross-platform development support extends to polished SDKs for web and mobile applications, facilitating seamless integration, high performance across devices, and offline map functionality crucial for areas with limited connectivity. 4.8 GapMaps GapMaps is a leading provider of cloud-based GIS mapping and location intelligence solutions. It empowers businesses to make informed decisions based on spatial data analysis. Its platform, GapMaps Live, offers a comprehensive suite of features tailored to various industries, including retail, healthcare, and real estate.GapMaps Live provides a user-friendly cloud-based platform for real-time data visualization and insights, facilitating customizable catchments for understanding customer behavior and optimizing store locations. Competitive analysis tools allow businesses to assess competitor locations and gain strategic insights. GapMaps also offers GapAdvisory services, providing expert market planning, network, and growth strategies. GapInsite furnishes the latest industry intel, aiding businesses in understanding market conditions and customer behaviors. The GapMaps Connect Mobile App enables real-time field data collection and synchronization with GapMaps Live. Additionally, GapMaps offers comprehensive Point of Interest and demographics data globally, aiding businesses in market assessment and site selection. 4.9 Qlik Qlik offers a comprehensive data integration and analytics platform designed to empower organizations to leverage their data to drive business outcomes. With a range of tools and capabilities supporting data integration, real-time analytics, and artificial intelligence, Qlik provides a robust solution for businesses across various industries. Qlik Cloud Data Integration facilitates the creation of data pipelines to automate data movement and transformation alongside modern analytics capabilities such as self-service analytics and interactive dashboards. Qlik Sense, powered by its associative engine, enables users to explore data freely and generate insights efficiently through innovative visualizations and continuous learning resources like Qlik Continuous Classroom. The platform also emphasizes data quality and governance, ensuring data accuracy, completeness, and reliability while promoting a unified approach to management. Qlik Application Automation offers a no-code automation interface to seamlessly build automated analytics and data workflows. 4.10 Connectbase Connectbase offers a comprehensive platform called ‘The Connected World,’ designed to revolutionize the buying and selling of network connectivity through advanced location intelligence and automation. Tailored to improve efficiency and accuracy for network providers, this platform enables better decision-making and streamlined processes. Connectbase provides highly accurate, location-specific data for over 1.4 billion buildings worldwide, including insights into building structures, tenant information, and competitive geography. Continuous updates ensure users have the most current information, reducing the risk of decision-making based on outdated data. The platform automates the quoting process, enabling quick and accurate responses to deals and eliminating delays caused by manual methods. Configure, Price, Quote (CPQ) functionality facilitates scalable, real-time quoting from configurable supplier product catalogs. Users can leverage real-time market and revenue data to make informed decisions about where to build new routes and expand their network, optimizing ROI. Tools for prospecting and pricing based on detailed market insights help businesses target sales efforts and maximize profitability. Centralized management of partner-building lists and product catalogs streamlines buying and selling processes. 5. Wrap Up Location intelligence offers numerous benefits for businesses, including risk management, predictive analytics, and real-time trend tracking. It facilitates streamlined operations and services, enhancing efficiency across various functions. With the increasing digitization of business processes, organizations can gather more user information, driving further industry growth. Particularly for customer-facing businesses, leveraging real-time location data improves the in-store experience significantly. From sales and marketing to customer and facility management, location intelligence presents plenty of opportunities for businesses to optimize their operations and enhance their competitive edge. Looking ahead, the future of location intelligence promises even more incredible advancements and opportunities for businesses. As technology evolves, we can expect enhanced precision and granularity in location data, enabling more accurate predictive analytics and risk management strategies. Integrating location intelligence with emerging technologies such as artificial intelligence and augmented reality will unlock new dimensions of customer engagement and personalized experiences. Moreover, with the increase of Internet of Things devices, businesses will have access to vast streams of real-time location data, empowering them to make proactive decisions and stay ahead in a dynamic market. Embracing these developments, businesses can remain agile, responsive, and poised for success in the ever-evolving digital ecosystem.

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Spotlight

Careerera

Careerera is an online education provider company of professional certification training, based in Herndon, Virginia, USA. Careerera is regarded as one of the front-runners in offering qualitative online courses to the ones who really wish to go ahead in their career by earning quality certifications. All the certification courses provided by us are in complete sync with the liking and requirements of the students.

Related News

Big Data

Airbyte Racks Up Awards from InfoWorld, BigDATAwire, Built In; Builds Largest and Fastest-Growing User Community

Airbyte | January 30, 2024

Airbyte, creators of the leading open-source data movement infrastructure, today announced a series of accomplishments and awards reinforcing its standing as the largest and fastest-growing data movement community. With a focus on innovation, community engagement, and performance enhancement, Airbyte continues to revolutionize the way data is handled and processed across industries. “Airbyte proudly stands as the front-runner in the data movement landscape with the largest community of more than 5,000 daily users and over 125,000 deployments, with monthly data synchronizations of over 2 petabytes,” said Michel Tricot, co-founder and CEO, Airbyte. “This unparalleled growth is a testament to Airbyte's widespread adoption by users and the trust placed in its capabilities.” The Airbyte community has more than 800 code contributors and 12,000 stars on GitHub. Recently, the company held its second annual virtual conference called move(data), which attracted over 5,000 attendees. Airbyte was named an InfoWorld Technology of the Year Award finalist: Data Management – Integration (in October) for cutting-edge products that are changing how IT organizations work and how companies do business. And, at the start of this year, was named to the Built In 2024 Best Places To Work Award in San Francisco – Best Startups to Work For, recognizing the company's commitment to fostering a positive work environment, remote and flexible work opportunities, and programs for diversity, equity, and inclusion. Today, the company received the BigDATAwire Readers/Editors Choice Award – Big Data and AI Startup, which recognizes companies and products that have made a difference. Other key milestones in 2023 include the following. Availability of more than 350 data connectors, making Airbyte the platform with the most connectors in the industry. The company aims to increase that to 500 high-quality connectors supported by the end of this year. More than 2,000 custom connectors were created with the Airbyte No-Code Connector Builder, which enables data connectors to be made in minutes. Significant performance improvement with database replication speed increased by 10 times to support larger datasets. Added support for five vector databases, in addition to unstructured data sources, as the first company to build a bridge between data movement platforms and artificial intelligence (AI). Looking ahead, Airbyte will introduce data lakehouse destinations, as well as a new Publish feature to push data to API destinations. About Airbyte Airbyte is the open-source data movement infrastructure leader running in the safety of your cloud and syncing data from applications, APIs, and databases to data warehouses, lakes, and other destinations. Airbyte offers four products: Airbyte Open Source, Airbyte Self-Managed, Airbyte Cloud, and Powered by Airbyte. Airbyte was co-founded by Michel Tricot (former director of engineering and head of integrations at Liveramp and RideOS) and John Lafleur (serial entrepreneur of dev tools and B2B). The company is headquartered in San Francisco with a distributed team around the world. To learn more, visit airbyte.com.

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Big Data Management

The Modern Data Company Recognized in Gartner's Magic Quadrant for Data Integration

The Modern Data Company | January 23, 2024

The Modern Data Company, recognized for its expertise in developing and managing advanced data products, is delighted to announce its distinction as an honorable mention in Gartner's 'Magic Quadrant for Data Integration Tools,' powered by our leading product, DataOS. “This accolade underscores our commitment to productizing data and revolutionizing data management technologies. Our focus extends beyond traditional data management, guiding companies on their journey to effectively utilize data, realize tangible ROI on their data investments, and harness advanced technologies such as AI, ML, and Large Language Models (LLMs). This recognition is a testament to Modern Data’s alignment with the latest industry trends and our dedication to setting new standards in data integration and utilization.” – Srujan Akula, CEO of The Modern Data Company The inclusion in the Gartner report highlights The Modern Data Company's pivotal role in shaping the future of data integration. Our innovative approach, embodied in DataOS, enables businesses to navigate the complexities of data management, transforming data into a strategic asset. By simplifying data access and integration, we empower organizations to unlock the full potential of their data, driving insights and innovation without disruption. "Modern Data's recognition as an Honorable Mention in the Gartner MQ for Data Integration is a testament to the transformative impact their solutions have on businesses like ours. DataOS has been pivotal in allowing us to integrate multiple data sources, enabling our teams to have access to the data needed to make data driven decisions." – Emma Spight, SVP Technology, MIND 24-7 The Modern Data Company simplifies how organizations manage, access, and interact with data using its DataOS (data operating system) that unifies data silos, at scale. It provides ontology support, graph modeling, and a virtual data tier (e.g. a customer 360 model). From a technical point of view, it closes the gap from conceptual to physical data model. Users can define conceptually what they want and its software traverses and integrates data. DataOS provides a structured, repeatable approach to data integration that enhances agility and ensures high-quality outputs. This shift from traditional pipeline management to data products allows for more efficient data operations, as each 'product' is designed with a specific purpose and standardized interfaces, ensuring consistency across different uses and applications. With DataOS, businesses can expect a transformative impact on their data strategies, marked by increased efficiency and a robust framework for handling complex data ecosystems, allowing for more and faster iterations of conceptual models. About The Modern Data Company The Modern Data Company, with its flagship product DataOS, revolutionizes the creation of data products. DataOS® is engineered to build and manage comprehensive data products to foster data mesh adoption, propelling organizations towards a data-driven future. DataOS directly addresses key AI/ML and LLM challenges: ensuring quality data, scaling computational resources, and integrating seamlessly into business processes. In our commitment to provide open systems, we have created an open data developer platform specification that is gaining wide industry support.

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Big Data Management

data.world Integrates with Snowflake Data Quality Metrics to Bolster Data Trust

data.world | January 24, 2024

data.world, the data catalog platform company, today announced an integration with Snowflake, the Data Cloud company, that brings new data quality metrics and measurement capabilities to enterprises. The data.world Snowflake Collector now empowers enterprise data teams to measure data quality across their organization on-demand, unifying data quality and analytics. Customers can now achieve greater trust in their data quality and downstream analytics to support mission-critical applications, confident data-driven decision-making, and AI initiatives. Data quality remains one of the top concerns for chief data officers and a critical barrier to creating a data-driven culture. Traditionally, data quality assurance has relied on manual oversight – a process that’s tedious and fraught with inefficacy. The data.world Data Catalog Platform now delivers Snowflake data quality metrics directly to customers, streamlining quality assurance timelines and accelerating data-first initiatives. Data consumers can access contextual information in the catalog or directly within tools such as Tableau and PowerBI via Hoots – data.world’s embedded trust badges – that broadcast data health status and catalog context, bolstering transparency and trust. Additionally, teams can link certification and DataOps workflows to Snowflake's data quality metrics to automate manual workflows and quality alerts. Backed by a knowledge graph architecture, data.world provides greater insight into data quality scores via intelligence on data provenance, usage, and context – all of which support DataOps and governance workflows. “Data trust is increasingly crucial to every facet of business and data teams are struggling to verify the quality of their data, facing increased scrutiny from developers and decision-makers alike on the downstream impacts of their work, including analytics – and soon enough, AI applications,” said Jeff Hollan, Director, Product Management at Snowflake. “Our collaboration with data.world enables data teams and decision-makers to verify and trust their data’s quality to use in mission-critical applications and analytics across their business.” “High-quality data has always been a priority among enterprise data teams and decision-makers. As enterprise AI ambitions grow, the number one priority is ensuring the data powering generative AI is clean, consistent, and contextual,” said Bryon Jacob, CTO at data.world. “Alongside Snowflake, we’re taking steps to ensure data scientists, analysts, and leaders can confidently feed AI and analytics applications data that delivers high-quality insights, and supports the type of decision-making that drives their business forward.” The integration builds on the robust collaboration between data.world and Snowflake. Most recently, the companies announced an exclusive offering for joint customers, streamlining adoption timelines and offering a new attractive price point. The data.world's knowledge graph-powered data catalog already offers unique benefits for Snowflake customers, including support for Snowpark. This offering is now available to all data.world enterprise customers using the Snowflake Collector, as well as customers taking advantage of the Snowflake-only offering. To learn more about the data quality integration or the data.world data catalog platform, visit data.world. About data.world data.world is the data catalog platform built for your AI future. Its cloud-native SaaS (software-as-a-service) platform combines a consumer-grade user experience with a powerful Knowledge Graph to deliver enhanced data discovery, agile data governance, and actionable insights. data.world is a Certified B Corporation and public benefit corporation and home to the world’s largest collaborative open data community with more than two million members, including ninety percent of the Fortune 500. Our company has 76 patents and has been named one of Austin’s Best Places to Work seven years in a row.

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Big Data

Airbyte Racks Up Awards from InfoWorld, BigDATAwire, Built In; Builds Largest and Fastest-Growing User Community

Airbyte | January 30, 2024

Airbyte, creators of the leading open-source data movement infrastructure, today announced a series of accomplishments and awards reinforcing its standing as the largest and fastest-growing data movement community. With a focus on innovation, community engagement, and performance enhancement, Airbyte continues to revolutionize the way data is handled and processed across industries. “Airbyte proudly stands as the front-runner in the data movement landscape with the largest community of more than 5,000 daily users and over 125,000 deployments, with monthly data synchronizations of over 2 petabytes,” said Michel Tricot, co-founder and CEO, Airbyte. “This unparalleled growth is a testament to Airbyte's widespread adoption by users and the trust placed in its capabilities.” The Airbyte community has more than 800 code contributors and 12,000 stars on GitHub. Recently, the company held its second annual virtual conference called move(data), which attracted over 5,000 attendees. Airbyte was named an InfoWorld Technology of the Year Award finalist: Data Management – Integration (in October) for cutting-edge products that are changing how IT organizations work and how companies do business. And, at the start of this year, was named to the Built In 2024 Best Places To Work Award in San Francisco – Best Startups to Work For, recognizing the company's commitment to fostering a positive work environment, remote and flexible work opportunities, and programs for diversity, equity, and inclusion. Today, the company received the BigDATAwire Readers/Editors Choice Award – Big Data and AI Startup, which recognizes companies and products that have made a difference. Other key milestones in 2023 include the following. Availability of more than 350 data connectors, making Airbyte the platform with the most connectors in the industry. The company aims to increase that to 500 high-quality connectors supported by the end of this year. More than 2,000 custom connectors were created with the Airbyte No-Code Connector Builder, which enables data connectors to be made in minutes. Significant performance improvement with database replication speed increased by 10 times to support larger datasets. Added support for five vector databases, in addition to unstructured data sources, as the first company to build a bridge between data movement platforms and artificial intelligence (AI). Looking ahead, Airbyte will introduce data lakehouse destinations, as well as a new Publish feature to push data to API destinations. About Airbyte Airbyte is the open-source data movement infrastructure leader running in the safety of your cloud and syncing data from applications, APIs, and databases to data warehouses, lakes, and other destinations. Airbyte offers four products: Airbyte Open Source, Airbyte Self-Managed, Airbyte Cloud, and Powered by Airbyte. Airbyte was co-founded by Michel Tricot (former director of engineering and head of integrations at Liveramp and RideOS) and John Lafleur (serial entrepreneur of dev tools and B2B). The company is headquartered in San Francisco with a distributed team around the world. To learn more, visit airbyte.com.

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Big Data Management

The Modern Data Company Recognized in Gartner's Magic Quadrant for Data Integration

The Modern Data Company | January 23, 2024

The Modern Data Company, recognized for its expertise in developing and managing advanced data products, is delighted to announce its distinction as an honorable mention in Gartner's 'Magic Quadrant for Data Integration Tools,' powered by our leading product, DataOS. “This accolade underscores our commitment to productizing data and revolutionizing data management technologies. Our focus extends beyond traditional data management, guiding companies on their journey to effectively utilize data, realize tangible ROI on their data investments, and harness advanced technologies such as AI, ML, and Large Language Models (LLMs). This recognition is a testament to Modern Data’s alignment with the latest industry trends and our dedication to setting new standards in data integration and utilization.” – Srujan Akula, CEO of The Modern Data Company The inclusion in the Gartner report highlights The Modern Data Company's pivotal role in shaping the future of data integration. Our innovative approach, embodied in DataOS, enables businesses to navigate the complexities of data management, transforming data into a strategic asset. By simplifying data access and integration, we empower organizations to unlock the full potential of their data, driving insights and innovation without disruption. "Modern Data's recognition as an Honorable Mention in the Gartner MQ for Data Integration is a testament to the transformative impact their solutions have on businesses like ours. DataOS has been pivotal in allowing us to integrate multiple data sources, enabling our teams to have access to the data needed to make data driven decisions." – Emma Spight, SVP Technology, MIND 24-7 The Modern Data Company simplifies how organizations manage, access, and interact with data using its DataOS (data operating system) that unifies data silos, at scale. It provides ontology support, graph modeling, and a virtual data tier (e.g. a customer 360 model). From a technical point of view, it closes the gap from conceptual to physical data model. Users can define conceptually what they want and its software traverses and integrates data. DataOS provides a structured, repeatable approach to data integration that enhances agility and ensures high-quality outputs. This shift from traditional pipeline management to data products allows for more efficient data operations, as each 'product' is designed with a specific purpose and standardized interfaces, ensuring consistency across different uses and applications. With DataOS, businesses can expect a transformative impact on their data strategies, marked by increased efficiency and a robust framework for handling complex data ecosystems, allowing for more and faster iterations of conceptual models. About The Modern Data Company The Modern Data Company, with its flagship product DataOS, revolutionizes the creation of data products. DataOS® is engineered to build and manage comprehensive data products to foster data mesh adoption, propelling organizations towards a data-driven future. DataOS directly addresses key AI/ML and LLM challenges: ensuring quality data, scaling computational resources, and integrating seamlessly into business processes. In our commitment to provide open systems, we have created an open data developer platform specification that is gaining wide industry support.

Read More

Big Data Management

data.world Integrates with Snowflake Data Quality Metrics to Bolster Data Trust

data.world | January 24, 2024

data.world, the data catalog platform company, today announced an integration with Snowflake, the Data Cloud company, that brings new data quality metrics and measurement capabilities to enterprises. The data.world Snowflake Collector now empowers enterprise data teams to measure data quality across their organization on-demand, unifying data quality and analytics. Customers can now achieve greater trust in their data quality and downstream analytics to support mission-critical applications, confident data-driven decision-making, and AI initiatives. Data quality remains one of the top concerns for chief data officers and a critical barrier to creating a data-driven culture. Traditionally, data quality assurance has relied on manual oversight – a process that’s tedious and fraught with inefficacy. The data.world Data Catalog Platform now delivers Snowflake data quality metrics directly to customers, streamlining quality assurance timelines and accelerating data-first initiatives. Data consumers can access contextual information in the catalog or directly within tools such as Tableau and PowerBI via Hoots – data.world’s embedded trust badges – that broadcast data health status and catalog context, bolstering transparency and trust. Additionally, teams can link certification and DataOps workflows to Snowflake's data quality metrics to automate manual workflows and quality alerts. Backed by a knowledge graph architecture, data.world provides greater insight into data quality scores via intelligence on data provenance, usage, and context – all of which support DataOps and governance workflows. “Data trust is increasingly crucial to every facet of business and data teams are struggling to verify the quality of their data, facing increased scrutiny from developers and decision-makers alike on the downstream impacts of their work, including analytics – and soon enough, AI applications,” said Jeff Hollan, Director, Product Management at Snowflake. “Our collaboration with data.world enables data teams and decision-makers to verify and trust their data’s quality to use in mission-critical applications and analytics across their business.” “High-quality data has always been a priority among enterprise data teams and decision-makers. As enterprise AI ambitions grow, the number one priority is ensuring the data powering generative AI is clean, consistent, and contextual,” said Bryon Jacob, CTO at data.world. “Alongside Snowflake, we’re taking steps to ensure data scientists, analysts, and leaders can confidently feed AI and analytics applications data that delivers high-quality insights, and supports the type of decision-making that drives their business forward.” The integration builds on the robust collaboration between data.world and Snowflake. Most recently, the companies announced an exclusive offering for joint customers, streamlining adoption timelines and offering a new attractive price point. The data.world's knowledge graph-powered data catalog already offers unique benefits for Snowflake customers, including support for Snowpark. This offering is now available to all data.world enterprise customers using the Snowflake Collector, as well as customers taking advantage of the Snowflake-only offering. To learn more about the data quality integration or the data.world data catalog platform, visit data.world. About data.world data.world is the data catalog platform built for your AI future. Its cloud-native SaaS (software-as-a-service) platform combines a consumer-grade user experience with a powerful Knowledge Graph to deliver enhanced data discovery, agile data governance, and actionable insights. data.world is a Certified B Corporation and public benefit corporation and home to the world’s largest collaborative open data community with more than two million members, including ninety percent of the Fortune 500. Our company has 76 patents and has been named one of Austin’s Best Places to Work seven years in a row.

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