Big Data Analytics for Security Intelligence

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The technological advances in storage, processing, and analysis of Big Data include (a) the rapidly decreasing cost of storage and CPU power in recent years; (b) the flexibility and cost-effectiveness of datacenters and cloud computing for elastic computation and storage; and (c) the development of new frameworks such as Hadoop, which allow users to take advantage of these distributed computing systems storing large quantities of data through flexible parallel processing. These advances have created several differences between traditional analytics and Big Data analytics.

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Flashpoint

Flashpoint delivers Business Risk Intelligence (BRI) to empower organizations worldwide with meaningful intelligence and information that combats threats and adversaries. The company’s sophisticated technology, advanced data collections, and human-powered analysis uniquely enables large enterprises and the public sector to bolster cybersecurity, confront fraud, detect insider threats and build insider threat programs, enhance physical security, improve executive protection, and address vendor risk and supply chain integrity.

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BIG DATA MANAGEMENT

Why Adaptive AI Can Overtake Traditional AI

Article | July 6, 2022

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.

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BIG DATA MANAGEMENT

Data-Centric Approach for AI Development

Article | July 11, 2022

As AI has grown in popularity over the past decade, practitioners have concentrated on gathering as much data as possible, classifying it, preparing it for usage, and then iterating on model architectures and hyper-parameters to attain our desired objectives. While dealing with all of this data has long been known as laborious and time-consuming, it has typically been seen as an upfront, one-time step we take before entering into the essential modeling phase of machine learning. Data quality concerns, label noise, model drift, and other biases are all addressed in the same way: by collecting and labeling more data, followed by additional model iterations. The foregoing technique has worked successfully for firms with unlimited resources or strategic challenges. It doesn't work well for machine learning's long-tail issues, particularly those with fewer users and little training data. The discovery that the prevailing method of deep learning doesn't "scale down" to industry challenges has given birth to a new "trend" in the area termed "Data-Centric AI." Implementing a Data-Centric Approach for AI Development Leverage MLOps Practices Data-centric AI prioritizes data over models. Model selection, hyper-parameter tuning, experiment tracking, deployment, and monitoring take time. Data-centric approaches emphasize automating and simplifying ML lifecycle operations. Standardizing and automating model-building requires MLOps. MLOps automates machine learning lifecycle management pipelines. An organizational structure improves communication and cooperation. Involve Domain Expertise Data-centric AI development requires domain-specific datasets. Data scientists can overlook intricacies in various sectors, business processes, or even the same domain. Domain experts can give ground truth for the AI use case and verify whether the dataset truly portrays the situation. Complete and Accurate Data Data gaps cause misleading results. It's crucial to have a training dataset that correctly depicts the underlying real-world phenomenon. Data augmentation or creating synthetic data might be helpful if gathering comprehensive and representative data is costly or challenging for your use case.

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BIG DATA MANAGEMENT,DATA VISUALIZATION,DATA ARCHITECTURE

A Modern Application Must Have: Multi-cloud Database

Article | August 18, 2022

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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BIG DATA MANAGEMENT

Why Increasing Data Maturity Help Businesses Unlock Digital Potential?

Article | July 5, 2022

There is no dispute that brands that harness and invest in data capabilities will be the ones to realize their maximum revenue potential. However, while today's marketers have access to a multitude of data sources, understanding what data to use and how to utilize it are two of the biggest challenges for all. Data utilization in companies is an inconsistent experience. Some businesses have sensibly invested in improving their data maturity. They can pivot quickly to maximize income potential in an unstable economic environment. Others face a cycle of declining returns as they try to reproduce previous achievements with variable outcomes. Importance of Data Maturity for Businesses Understanding your organization's data maturity is critical for five reasons. An understanding of data maturity may assist marketers in: Align Recognize which problems and challenges the wider organization is attempting to solve and modify techniques to support those goals. Appreciate Analyze honestly what the company is good at doing presently and where adjustments are needed to create better data decision-making. Evaluate Measure data literacy levels while implementing training and upskilling resources to facilitate the implementation of an open learning environment to encourage innovative thinking. Anticipate As the company's data capabilities develop, look forward to significantly advanced analytics possibilities. Calibrate Optimize technology and infrastructure to extract maximum value now while also appropriately planning for future resources. Future-Proof Your Business with Data Maturity Data maturity applies to the whole organization. It is a company-wide effort that extends beyond the goals of a single sales or marketing team. As a result, it's critical to bring together diverse internal influencers to determine how improvements to your data strategy can assist everyone in achieving the same objectives. The mix of stakeholders is unique to each organization, so it will be determined by your company's priorities.

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Spotlight

Flashpoint

Flashpoint delivers Business Risk Intelligence (BRI) to empower organizations worldwide with meaningful intelligence and information that combats threats and adversaries. The company’s sophisticated technology, advanced data collections, and human-powered analysis uniquely enables large enterprises and the public sector to bolster cybersecurity, confront fraud, detect insider threats and build insider threat programs, enhance physical security, improve executive protection, and address vendor risk and supply chain integrity.

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BUSINESS INTELLIGENCE,BIG DATA MANAGEMENT,DATA SCIENCE

Makersite Announces Sustainability Analytics Partnership With Autodesk

Makersite | September 28, 2022

Makersite, a world leader in bringing sustainability and cost insights into the early stage design process for the world’s leading brands, today announced partnering with Autodesk, the leader in product design software. The new partnership combines Makersite’s environmental impact and cost data with Autodesk Fusion 360’s product design data. Sustainability begins at the heart of the product: its design phase. Still, less than 1% of products have sustainability as a design parameter. Even though the general public’s wish for sustainable products grows and emission regulations worldwide are becoming more and more, incorporating sustainability at the design level has been a challenge for most product designers in the past. Makersite’s partnership with Autodesk is changing this. The new Fusion 360 plug-in features: Allows designers to have Makersite instantly calculate the environmental and cost impacts of their design at the push of a button Gives Fusion 360 users access to over 300 materials, cost, and sustainability insights based on the used structure, materials, and weight Provides enhanced data sets on over 50 decision criteria such as compliance, risk, health, and safety in real-time With this ground-breaking approach, product designers will no longer depend on experts or consultancies to design sustainable products. Instead, enterprise manufacturers will be able to use their own material masters and procurement data to enable teams to work toward sustainability goals led by design. This integration will enable more sustainable and successful designs, eliminate duplicative efforts and decrease time to market. “The stats tell us that 80% of the ecological impacts of a product are locked down in the design phase. Therefore, the design phase of a product is the first and most necessary stage to get more sustainable goods into the world successfully,” shares Neil D’Souza, founder of Makersite. “However, eco-design is only feasible when designers have data about the sustainability of their product and its compliance, costing, environmental, health, and safety criteria. By integrating our data, AI, and calculation engines into Fusion, product designers are provided with clear and actionable insights so they can decide how to make their designs more sustainable,” D’Souza concludes. “It’s Autodesk’s intent to make designing for sustainability easily accessible, and ultimately intuitive, to product designers,” said Zoé Bezpalko, Autodesk Senior Design and Manufacturing Sustainability Manager. “By partnering with Makersite, we’ve created a holistic workflow within Fusion that provides insights into sustainable design directly within the design environment. Data-driven analysis from Makersite will enable manufacturers to make better decisions about creating safer, more sustainable products,” she said. “Companies are setting ambitious sustainability goals at high levels, sometimes as required by policy, but increasingly due to customer demand and as a source of competitive differentiation. The data that drives achieving those goals are often in disparate systems throughout the organization,” said Stephen Hooper, Autodesk Vice President & General Manager, Fusion 360. “We’re connecting relevant LCA data to the Fusion design workspace to help manufacturers meet their important sustainability goals,” said Hooper. Autodesk will hold its premier annual conference for product designers and manufacturers, Autodesk University, in New Orleans September 27-29, 2022. Makersite will take the stage with Zoé Bezpalko to present the plug-in to attendees during the conference. About Makersite Makersite's SaaS platform delivers enterprise digital twins to enable change in complex business environments. By intelligently mapping customers' product data via AI with live data from 140+ supply chain databases, Makersite instantly delivers deep-tier supply chain twins with 90%+ accuracy. Customers can assess the digital product twins across 30+ business criteria such as risk, sustainability, compliance, and cost. The platform has many applications, helping global enterprises build resilient supply chains, accelerate product innovation, and achieve NetZero.

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BUSINESS INTELLIGENCE,BIG DATA MANAGEMENT

Data Integration Platform Dataddo Launches First-Ever Free Plan with No Extraction Limits

Dataddo | September 28, 2022

Dataddo, an SaaS startup that provides an automated, no-code data integration platform, today announced the launch of its Free plan—the first-ever free data integration plan with no extraction limits. This is a no-investment way for any professional, regardless of technical skill, to access and start working with data from disparate sources. The plan comes as a response to company cultural obstacles that hinder adoption of data initiatives within organizations across industries, such as low data literacy. For at least the last five years, the grand majority of leading companies across industries has been investing in data initiatives, with the percentage today being as high as 97%. Yet only 26.5% of these companies claim to actually be data-driven. Mounting evidence suggests that the main reason for this discrepancy is company culture, meaning both lack of executive buy-in on initiatives and lack of employee confidence in data skills. In a recent survey by Accenture of 9,000 employees from companies across industries, nearly three quarters of respondents (74%) claimed to feel “overwhelmed or unhappy when working with data.” This is critical because, as Gartner states, “the real drivers of [data-driven culture] are the people.” Dataddo’s Free plan aims to help businesses overcome these obstacles by making it easier for them to share data and familiarize employees with visualization tools before investing in paid tools. The plan is the first free data integration plan on the market that puts no cap on extraction limits, and it can be used for an unlimited period of time. Under the plan, subscribers can access any ten of Dataddo’s 200+ connectors and automate the synchronization of any volume of marketing, sales, financial, and other cloud data to up to three dashboarding applications and/or Google Sheets weekly. The company offers a growing library of free templates for popular dashboarding applications, enabling professionals with any level of data skill to start analyzing immediately. The platform is SOC 2 Type II certified and compliant with all major data privacy laws around the globe, including ISO 27001, GDPR for Europe, CCPA and HIPAA in the US, LGPD for Brazil, POPIA for South Africa, and more.

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BIG DATA MANAGEMENT,DATA SCIENCE

Qlik Expands Strategic Alignment with Databricks Through SQL-Based Ingestion to Databricks Lakehouse and Partner Connect Integration

Qlik | September 27, 2022

Qlik® today announced two significant enhancements to its partnership with Databricks that make it easier than ever for customers to combine Qlik’s solutions and Databricks to advance their cloud analytics strategies. First is the launch of the Databricks Lakehouse (Delta) Endpoint, a new capability in Qlik Data Integration, which will simplify and improve customers' ability to ingest and deliver data to the Databricks Lakehouse. Second is the integration of Qlik Cloud® with Databricks Partner Connect, enhancing the Qlik Data Analytics trial experience with Databricks. Both deepen and expand the ability of customers to combine Qlik and Databricks in their efforts to leverage the cloud for impact. “We’re excited about the potential of Qlik’s Databricks Lakehouse (Delta) Endpoint to seamlessly and efficiently deliver the data customers need to drive more value from their investment in the Databricks Lakehouse. “And, with Qlik Analytics now integrated with Databricks Partner Connect, we are making it even easier for customers to discover, use and share data-driven insights across their organizations.” Roger Murff, VP of Technology Partners at Databricks Leveraging Databricks SQL, Qlik’s Databricks (Delta) Endpoint optimizes the continuous and real-time data ingestion through Qlik Data Integration into Delta Lake on Databricks. This gives organizations the ability to cost effectively drive more data from a wide range of enterprise data sources, including SAP and Mainframe, into the Databricks Lakehouse while leveraging their cloud provider of choice such as Amazon Web Services (AWS), Google Cloud Platform (GCP) or Microsoft Azure. Qlik has also recently integrated Qlik Cloud with Databricks Partner Connect. Databricks customers can now seamlessly experience Qlik Sense® SaaS within the Databricks Lakehouse Platform through an existing Qlik tenant or a free Qlik trial. The experience includes automatic configuration of connectivity to the customer’s Databricks environment, making it easier for Databricks customers to experience the power of Qlik Cloud. Both the new Databricks Lakehouse (Delta) Endpoint and Partner Connect integration demonstrate Qlik’s commitment to supporting customers like J.B. Hunt in their efforts to combine Qlik and Databricks for impact. “We’re seeing more demand for real-time data related to shippers and carriers in order to provide up-to-the-minute information on how they are performing. Qlik and Databricks help us to meet those demands,” said Joe Spinelle, Director of Engineering and Technology at J.B. Hunt. “As they migrate more and more to the cloud, Databricks customers want strategic partners that make it as easy as possible to deliver and analyze data for impact,” said Itamar Ankorion, SVP of Technology Alliances at Qlik. “With our new Databricks Lakehouse Endpoint and Databricks Partner Connect integration, Qlik is clearly demonstrating its alignment with Databricks and our dedication to the Databricks community to deliver an amazing experience that furthers their overall data strategies.” About Qlik Qlik’s vision is a data-literate world, where everyone can use data and analytics to improve decision-making and solve their most challenging problems. A private company, Qlik offers real-time data integration and analytics solutions, powered by Qlik Cloud®, to close the gaps between data, insights and action. By transforming data into Active Intelligence, businesses can drive better decisions, improve revenue and profitability, and optimize customer relationships. Qlik serves more than 38,000 active customers in over 100 countries.

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BUSINESS INTELLIGENCE,BIG DATA MANAGEMENT,DATA SCIENCE

Makersite Announces Sustainability Analytics Partnership With Autodesk

Makersite | September 28, 2022

Makersite, a world leader in bringing sustainability and cost insights into the early stage design process for the world’s leading brands, today announced partnering with Autodesk, the leader in product design software. The new partnership combines Makersite’s environmental impact and cost data with Autodesk Fusion 360’s product design data. Sustainability begins at the heart of the product: its design phase. Still, less than 1% of products have sustainability as a design parameter. Even though the general public’s wish for sustainable products grows and emission regulations worldwide are becoming more and more, incorporating sustainability at the design level has been a challenge for most product designers in the past. Makersite’s partnership with Autodesk is changing this. The new Fusion 360 plug-in features: Allows designers to have Makersite instantly calculate the environmental and cost impacts of their design at the push of a button Gives Fusion 360 users access to over 300 materials, cost, and sustainability insights based on the used structure, materials, and weight Provides enhanced data sets on over 50 decision criteria such as compliance, risk, health, and safety in real-time With this ground-breaking approach, product designers will no longer depend on experts or consultancies to design sustainable products. Instead, enterprise manufacturers will be able to use their own material masters and procurement data to enable teams to work toward sustainability goals led by design. This integration will enable more sustainable and successful designs, eliminate duplicative efforts and decrease time to market. “The stats tell us that 80% of the ecological impacts of a product are locked down in the design phase. Therefore, the design phase of a product is the first and most necessary stage to get more sustainable goods into the world successfully,” shares Neil D’Souza, founder of Makersite. “However, eco-design is only feasible when designers have data about the sustainability of their product and its compliance, costing, environmental, health, and safety criteria. By integrating our data, AI, and calculation engines into Fusion, product designers are provided with clear and actionable insights so they can decide how to make their designs more sustainable,” D’Souza concludes. “It’s Autodesk’s intent to make designing for sustainability easily accessible, and ultimately intuitive, to product designers,” said Zoé Bezpalko, Autodesk Senior Design and Manufacturing Sustainability Manager. “By partnering with Makersite, we’ve created a holistic workflow within Fusion that provides insights into sustainable design directly within the design environment. Data-driven analysis from Makersite will enable manufacturers to make better decisions about creating safer, more sustainable products,” she said. “Companies are setting ambitious sustainability goals at high levels, sometimes as required by policy, but increasingly due to customer demand and as a source of competitive differentiation. The data that drives achieving those goals are often in disparate systems throughout the organization,” said Stephen Hooper, Autodesk Vice President & General Manager, Fusion 360. “We’re connecting relevant LCA data to the Fusion design workspace to help manufacturers meet their important sustainability goals,” said Hooper. Autodesk will hold its premier annual conference for product designers and manufacturers, Autodesk University, in New Orleans September 27-29, 2022. Makersite will take the stage with Zoé Bezpalko to present the plug-in to attendees during the conference. About Makersite Makersite's SaaS platform delivers enterprise digital twins to enable change in complex business environments. By intelligently mapping customers' product data via AI with live data from 140+ supply chain databases, Makersite instantly delivers deep-tier supply chain twins with 90%+ accuracy. Customers can assess the digital product twins across 30+ business criteria such as risk, sustainability, compliance, and cost. The platform has many applications, helping global enterprises build resilient supply chains, accelerate product innovation, and achieve NetZero.

Read More

BUSINESS INTELLIGENCE,BIG DATA MANAGEMENT

Data Integration Platform Dataddo Launches First-Ever Free Plan with No Extraction Limits

Dataddo | September 28, 2022

Dataddo, an SaaS startup that provides an automated, no-code data integration platform, today announced the launch of its Free plan—the first-ever free data integration plan with no extraction limits. This is a no-investment way for any professional, regardless of technical skill, to access and start working with data from disparate sources. The plan comes as a response to company cultural obstacles that hinder adoption of data initiatives within organizations across industries, such as low data literacy. For at least the last five years, the grand majority of leading companies across industries has been investing in data initiatives, with the percentage today being as high as 97%. Yet only 26.5% of these companies claim to actually be data-driven. Mounting evidence suggests that the main reason for this discrepancy is company culture, meaning both lack of executive buy-in on initiatives and lack of employee confidence in data skills. In a recent survey by Accenture of 9,000 employees from companies across industries, nearly three quarters of respondents (74%) claimed to feel “overwhelmed or unhappy when working with data.” This is critical because, as Gartner states, “the real drivers of [data-driven culture] are the people.” Dataddo’s Free plan aims to help businesses overcome these obstacles by making it easier for them to share data and familiarize employees with visualization tools before investing in paid tools. The plan is the first free data integration plan on the market that puts no cap on extraction limits, and it can be used for an unlimited period of time. Under the plan, subscribers can access any ten of Dataddo’s 200+ connectors and automate the synchronization of any volume of marketing, sales, financial, and other cloud data to up to three dashboarding applications and/or Google Sheets weekly. The company offers a growing library of free templates for popular dashboarding applications, enabling professionals with any level of data skill to start analyzing immediately. The platform is SOC 2 Type II certified and compliant with all major data privacy laws around the globe, including ISO 27001, GDPR for Europe, CCPA and HIPAA in the US, LGPD for Brazil, POPIA for South Africa, and more.

Read More

BIG DATA MANAGEMENT,DATA SCIENCE

Qlik Expands Strategic Alignment with Databricks Through SQL-Based Ingestion to Databricks Lakehouse and Partner Connect Integration

Qlik | September 27, 2022

Qlik® today announced two significant enhancements to its partnership with Databricks that make it easier than ever for customers to combine Qlik’s solutions and Databricks to advance their cloud analytics strategies. First is the launch of the Databricks Lakehouse (Delta) Endpoint, a new capability in Qlik Data Integration, which will simplify and improve customers' ability to ingest and deliver data to the Databricks Lakehouse. Second is the integration of Qlik Cloud® with Databricks Partner Connect, enhancing the Qlik Data Analytics trial experience with Databricks. Both deepen and expand the ability of customers to combine Qlik and Databricks in their efforts to leverage the cloud for impact. “We’re excited about the potential of Qlik’s Databricks Lakehouse (Delta) Endpoint to seamlessly and efficiently deliver the data customers need to drive more value from their investment in the Databricks Lakehouse. “And, with Qlik Analytics now integrated with Databricks Partner Connect, we are making it even easier for customers to discover, use and share data-driven insights across their organizations.” Roger Murff, VP of Technology Partners at Databricks Leveraging Databricks SQL, Qlik’s Databricks (Delta) Endpoint optimizes the continuous and real-time data ingestion through Qlik Data Integration into Delta Lake on Databricks. This gives organizations the ability to cost effectively drive more data from a wide range of enterprise data sources, including SAP and Mainframe, into the Databricks Lakehouse while leveraging their cloud provider of choice such as Amazon Web Services (AWS), Google Cloud Platform (GCP) or Microsoft Azure. Qlik has also recently integrated Qlik Cloud with Databricks Partner Connect. Databricks customers can now seamlessly experience Qlik Sense® SaaS within the Databricks Lakehouse Platform through an existing Qlik tenant or a free Qlik trial. The experience includes automatic configuration of connectivity to the customer’s Databricks environment, making it easier for Databricks customers to experience the power of Qlik Cloud. Both the new Databricks Lakehouse (Delta) Endpoint and Partner Connect integration demonstrate Qlik’s commitment to supporting customers like J.B. Hunt in their efforts to combine Qlik and Databricks for impact. “We’re seeing more demand for real-time data related to shippers and carriers in order to provide up-to-the-minute information on how they are performing. Qlik and Databricks help us to meet those demands,” said Joe Spinelle, Director of Engineering and Technology at J.B. Hunt. “As they migrate more and more to the cloud, Databricks customers want strategic partners that make it as easy as possible to deliver and analyze data for impact,” said Itamar Ankorion, SVP of Technology Alliances at Qlik. “With our new Databricks Lakehouse Endpoint and Databricks Partner Connect integration, Qlik is clearly demonstrating its alignment with Databricks and our dedication to the Databricks community to deliver an amazing experience that furthers their overall data strategies.” About Qlik Qlik’s vision is a data-literate world, where everyone can use data and analytics to improve decision-making and solve their most challenging problems. A private company, Qlik offers real-time data integration and analytics solutions, powered by Qlik Cloud®, to close the gaps between data, insights and action. By transforming data into Active Intelligence, businesses can drive better decisions, improve revenue and profitability, and optimize customer relationships. Qlik serves more than 38,000 active customers in over 100 countries.

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