This post is authored in conjunction with Bryan Saftler, Global Head of Marketing for Communications, Media & Entertainment at Databricks and Steve Sobel, Global Head - Communications, Media & Entertainment GTM at Databricks.
The communications industry is undergoing one of the most significant periods of growth (and change) in its 100+ year history. The dramatic increase in global traffic, the customer expectation for enhanced services, and the need for more network equipment is driving more complex and costly network management. In addition, data shows that as customers demand higher quality service and better customer experiences (CX), they’re more likely to churn when their needs are not met.
As a result, Communications Service Providers (CSPs) are looking to data and AI use cases to help reduce costs to serve and operate, develop and maintain great customer experiences, identify opportunities for revenue growth, and achieve scale with secure and reliable services. No small feat.
To illustrate this, look no further than the explosion of digital technologies — such as 5G, IoT, edge computing, and AI — which has ushered in a new era of big data. For example, according to Cisco's Visual Networking Index (VNI) Global Mobile Data Traffic Forecast, global mobile data traffic has grown to 77.5 exabytes per month. This growth is driven by the proliferation of mobile devices and the increasing demand for data-intensive applications. In addition, the number of connected IoT devices is skyrocketing. According to Statista, the number of connected IoT devices is expected to reach 31 billion by 2025, generating approximately 79.4 zettabytes of data annually. This data, while large and unwieldy, is critical to building a virtuous loop between networks and customers. By bringing this data together, CSPs can better understand the factors that contribute to a positive or negative customer experience.
To make this virtuous loop effective, the key is making sure that the right humans have access to the right data at the right moment in time. The need for a modern and unified data analytics and AI platform has never been greater. The problem? Traditional data architectures weren’t built to support Generative AI and machine learning use cases, especially across broad teams of data engineers, data scientists and analysts, while supporting the scale and agility communications companies need to handle evolving customer demands. This has led to heavy investments in modern data technologies and industry partnerships to use data more thoughtfully. This is achieved by:
Having a single view of all data in a unified architecture, including unstructured data like video, images and voice content.
Ensuring data is in a ready state for all analytics, AI, and ML use cases
Having a cloud infrastructure environment based on open source and open standards so IT and data teams can move with agility.
In a nutshell, ensuring all of your data is AI and business intelligence (BI) ready and being able to move fast to stay ahead of consumer and employee expectations is a critical strategy for every communications organization.
Introducing the Databricks Data Intelligence Platform on Azure for Communications
On Tuesday January 9th, we announced the world’s first Data Intelligence Platform with enhanced capabilities for the Communications industry for Databricks, including Azure Databricks. Built atop our Lakehouse architecture, the Data Intelligence Platform combines all the best features of a Data Lakehouse with generative AI capabilities. This means an open, unified foundation for all your data along with unprecedented access to analytics and AI across your organization.
We built the Databricks Data Intelligence Platform to help organizations better succeed with AI, democratize insights, and drive down costs. Teams can develop generative AI applications on their data without sacrificing data privacy or confidential IP. More humans across the organization can discover insights from more data in the language of their business. And teams can gain efficiency and simplify complexity by unifying data, governance, and AI together. This is only possible on a Data Intelligence Platform.
Databricks stands as a strategic partner for communications organizations. By leveraging the power of the Databricks Data Intelligence Platform, CSPs can gain a holistic view of their networks, operations, and customer interactions like never before. This newfound data-driven intelligence allows them to optimize network performance, predict and proactively address service disruptions, and deliver highly personalized customer experiences that drive loyalty and satisfaction. As data-driven enterprises, CSPs will be able to lead with innovation, deliver unmatched customer experiences, and pave the way for a connected future that transcends borders and boundaries.
Let’s talk through some of the biggest challenges around transforming into a data-driven communications organization (and how the Data Intelligence Platform addresses them):
Improving the Customer Experience
An organization's ability to deliver 1:1 personalization at scale goes a long way to meeting customers where they’re at, effectively mitigating churn. Unfortunately, legacy technologies are complex to manage and costly to scale for today’s massive volumes of customer data. AI and personalization at scale is impossible when you have fragmented views of an audience, lack real-time capabilities, and struggle to make the leap from descriptive to predictive analytics.
The Advantages of a Data Intelligence Platform: The Data Intelligence Platform for Communications enables teams to have a relationship with customers on their terms: a single, unified data platform where teams can perform the analysis needed to better understand sentiment across channels, create and deliver personalized recommendations, all with a robust ecosystem of data partners to deliver dynamic engagements in real-time that improve customer experience, increase profitability, and reduce churn.
Reducing the Cost to Serve/Operate
Complexity has driven increased costs across the board, which presents a twofold challenge. On one hand, the rapid pace of innovation requires constant upgrades and investments in new technologies. This results in higher initial capital expenditures and ongoing operational costs to remain at the forefront of technological advancements. On the other hand, legacy systems and outdated infrastructure can also be cost-intensive to maintain and integrate with newer technologies. The need for seamless interoperability between legacy and modern systems demands substantial resources, driving up operational expenses.
Additionally, the demand for seamless, high-quality customer experiences introduces cost pressures. As customers expect personalized, real-time services, organizations must invest in sophisticated customer relationship management (CRM) systems, data analytics tools, and AI-driven automation to provide tailored solutions. These investments, while enhancing customer satisfaction, can strain budgets and resources, especially if not carefully managed. Moreover, the necessity of robust cybersecurity measures to safeguard sensitive data against increasing cyber threats contributes to the escalating operational costs, requiring continuous investments in cybersecurity tools, personnel training, and risk mitigation strategies.
The Advantages of a Data Intelligence Platform: With data and AI on the same unified platform, teams can perform more intelligent network optimization and predictive maintenance, deploy robotic process automation, and push compute and AI to edge networks to reduce spend, save network bandwidth, and generate incremental revenue. Only a Data Intelligence Platform combines the unified data and governance benefits of a Data Lakehouse with the capabilities of generative AI.
Identifying New Revenue Sources
As traditional revenue streams such as voice and messaging face increased competition from new entrants, mobile virtual network operators (MVNO) and evolving customer preferences, organizations need to consider how diversification can mitigate risk. To address this challenge, teams must strategically leverage data and AI-driven insights to uncover untapped opportunities, anticipate market trends, and create innovative services that resonate with their customer base.
Here, data emerges as a valuable asset. With no shortage of customer data, network performance metrics, and usage patterns, organizations can leverage advanced analytics and AI to extract actionable insights that help teams better understand customer behavior, preferences, and pain points. This data-driven approach empowers teams to out-maneuver competition in an increasingly dynamic environment.
The Advantages of a Data Intelligence Platform on Azure: Built AI-first, the Databricks Data Intelligence Platform on Azure empowers organizations to tap the full potential of AI/ML workloads to forecast market trends, predict demand patterns, and simulate the impact of different business strategies. This empowers teams to make better-informed decisions on where to invest resources and which new revenue avenues to explore. In addition, the Data Intelligence Platform for Communications makes data sharing a first-class citizen within your enterprise, allowing organizations to share and monetize their data as a product. Tight integration with Microsoft Azure, means that Databricks' own Gen AI capabilities work seamlessly with leading Azure AI capabilities, including Azure Open AI.
Achieving Scale and Security
Striking a delicate balance between achieving profitable scale and ensuring robust security has become a multifaceted challenge. As communication service providers scale their networks and invest in cutting-edge technologies, they are met with the imperative to safeguard these investments against an increasingly sophisticated array of cyber threats. Simultaneously, the pressure to generate revenue while maintaining operational efficiency requires extracting more value from data and AI investments to optimize network performance, enhance customer experiences, and streamline operations.
The Advantages of a Data Intelligence Platform: Only Azure Databricks provides a single, unified data platform where data combines with the full potential of AI. Whether predicting network congestion, allocating resources efficiently, or optimizing bandwidth usage, teams building atop a Data Intelligence Platform can more easily achieve cost-effective scale without compromising quality of service.
Go from idea to proof-of-concept in weeks with pre-built solution accelerators
Built on top of our Data Intelligence Platform on Azure, Azure Databricks and our ecosystem of partners offer packaged solution accelerators to help organizations tackle the most common and high-value use cases in the industry. We’ve built a number of communications-specific accelerators that include:
Telco Network Analytics: Increase network reliability for the 5G+ era and reduce customer churn with robust pipelines and accurate forecasting
Customer Entity Resolution: Data generated through transactions, support center calls, and more can come together to form a 360-degree view of your customers
Behavioral Segmentation: Create advanced segments to drive better purchasing predictions based on behaviors
Recommendation Engines: Increase conversions and engagement with personalized omnichannel recommendations
Video Quality of Experience: Analyze batch and streaming data to ensure a performant content experience for streaming services
A growing partner ecosystem
Azure Databricks is working with industry-leading consulting and technology partners to enable best-in-class solutions. Azure Databricks helps customers across the communications industry ecosystem to reduce operational costs and improve customer engagement at a global scale. Azure Databricks has hundreds of joint Lakehouse customers, including T-Mobile, which uses Azure Databricks to more accurately determine construction readiness, ensure timely procurement of cell-site equipment, and identify fraud and waste of network materials; and AT&T, who uses the Databricks Data Intelligence Platform on Azure to protect its customer from fraud and increase operational efficiencies, benefiting both customers and the business.
Databricks Communications Implementation Partners: Databricks has also partnered with system integrators to deliver scalable industry solutions that help customers more rapidly address common use cases. Communications partners include Accenture, Amdocs, Capgemini, Slalom, and Tredence who have all worked with communications customers to help them enable the next generation of big data and AI use cases for communications leaders across the globe. Tailor-made for communication use cases, featured partner solutions include:
Accenture is investing in unique and differentiating telecommunications assets and accelerators built on Databricks that help their clients realize value faster. One of their largest projects was at a large global telecom, helping to build their enterprise data and AI foundation on Databricks. By implementing the Databricks Intelligence Platform and connecting their business, network, and operational data with Unity Catalog, the client has been able to accelerate ML and generative AI use cases that reduce churn, optimize 5G deployment, and accelerate their customer experience transformation.
Amdocs for Data Transformation: Leveraging the Amdocs Logical Data Model -- a TM Forum-certified communications-specific data model, which is optimized for modern technologies and near real-time processing -- Amdocs delivers an event-driven, scalable, consumption-ready data integration layer to help communications leaders with decision-making and creating more personalized customer experiences.
Tredence Telco.Atom.ai: An integrated accelerator ecosystem consisting of telecommunications-specific data models, pipelines, AI/ML code notebooks, front-end consumption layers, and a robust MLOps process, which allows telcos to develop and scale AI applications 50% faster.
“Generative AI has brought data to the forefront of discussions even among executives outside the data space. The ease of use and increasing value of generative AI applications have made data and AI more accessible to business-focused leaders. This convergence of art and science in creative processes, such as AI-driven content creation, marks an exciting development in the industry.”
Manish Dasaur, Chief Data and Analytics Officer, Comms and Media, North America, Accenture
“The telecommunications industry is in the midst of major transformation, driven by factors like 5G (with 6G on the horizon) and next-generation networks, convergence with other industries, and shifting customer expectations. Capgemini has successfully implemented Databricks architecture for our telecommunication clients, facilitating data-driven decisions across customer care, network, field operations, and many more business domains. Lakehouse architecture can play a pivotal role in building a highly scalable data and analytics platform to unlock significant value, perform comprehensive network coverage analysis, improve customer experience, and adapt to ever-changing telecommunications landscape.”
Pankaj Kaul, Insights and Data Leader (Telecommunication, Media, Technology, and Digital), Capgemini
Databricks Communications Technology Partners: Our technology partners are critical to success and augment Databricks with industry-specific capability. Communications customers are leveraging Azure Databricks technology partners as they look to improve their consumer, network and employee experiences and deliver advanced analytics and machine learning solutions.
Want to learn more about the Databricks Data Intelligence Platform on Azure for Communications? Click here for our solutions page. We’re thrilled to continue to invest in the Communications industry, empowering leaders put data, AI and analytics at the very center of their organization.
Published Feb 06, 2024
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Powering the data and AI-driven future of the Communications Industry with the
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This post is authored in conjunction with Bryan Saftler, Global Head of Marketing for Communications, Media & Entertainment at Databricks and Steve Sobel, Global Head - Communications, Media & Entertainment GTM at Databricks.
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The communications industry is undergoing one of the most significant periods of growth (and change) in its 100+ year history. The dramatic increase in global traffic, the customer expectation for enhanced services, and the need for more network equipment is driving more complex and costly network management. In addition, data shows that as customers demand higher quality service and better customer experiences (CX), they’re more likely to churn when their needs are not met.
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As a result, Communications Service Providers (CSPs) are looking to data and AI use cases to help reduce costs to serve and operate, develop and maintain great customer experiences, identify opportunities for revenue growth, and achieve scale with secure and reliable services. No small feat.
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To illustrate this, look no further than the explosion of digital technologies — such as 5G, IoT, edge computing, and AI — which has ushered in a new era of big data. For example, according to Cisco's Visual Networking Index (VNI) Global Mobile Data Traffic Forecast, global mobile data traffic has grown to 77.5 exabytes per month. This growth is driven by the proliferation of mobile devices and the increasing demand for data-intensive applications. In addition, the number of connected IoT devices is skyrocketing. According to Statista, the number of connected IoT devices is expected to reach 31 billion by 2025, generating approximately 79.4 zettabytes of data annually. This data, while large and unwieldy, is critical to building a virtuous loop between networks and customers. By bringing this data together, CSPs can better understand the factors that contribute to a positive or negative customer experience.
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To make this virtuous loop effective, the key is making sure that the right humans have access to the right data at the right moment in time. The need for a modern and unified data analytics and AI platform has never been greater. The problem? Traditional data architectures weren’t built to support Generative AI and machine learning use cases, especially across broad teams of data engineers, data scientists and analysts, while supporting the scale and agility communications companies need to handle evolving customer demands. This has led to heavy investments in modern data technologies and industry partnerships to use data more thoughtfully. This is achieved by:
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Having a single view of all data in a unified architecture, including unstructured data like video, images and voice content.
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Ensuring data is in a ready state for all analytics, AI, and ML use cases
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Having a cloud infrastructure environment based on open source and open standards so IT and data teams can move with agility.
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In a nutshell, ensuring all of your data is AI and business intelligence (BI) ready and being able to move fast to stay ahead of consumer and employee expectations is a critical strategy for every communications organization.
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Introducing the Databricks Data Intelligence Platform on Azure for Communications
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On Tuesday January 9th, we announced the world’s first Data Intelligence Platform with enhanced capabilities for the Communications industry for Databricks, including Azure Databricks. Built atop our Lakehouse architecture, the Data Intelligence Platform combines all the best features of a Data Lakehouse with generative AI capabilities. This means an open, unified foundation for all your data along with unprecedented access to analytics and AI across your organization.
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We built the Databricks Data Intelligence Platform to help organizations better succeed with AI, democratize insights, and drive down costs. Teams can develop generative AI applications on their data without sacrificing data privacy or confidential IP. More humans across the organization can discover insights from more data in the language of their business. And teams can gain efficiency and simplify complexity by unifying data, governance, and AI together. This is only possible on a Data Intelligence Platform.
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Databricks stands as a strategic partner for communications organizations. By leveraging the power of the Databricks Data Intelligence Platform, CSPs can gain a holistic view of their networks, operations, and customer interactions like never before. This newfound data-driven intelligence allows them to optimize network performance, predict and proactively address service disruptions, and deliver highly personalized customer experiences that drive loyalty and satisfaction. As data-driven enterprises, CSPs will be able to lead with innovation, deliver unmatched customer experiences, and pave the way for a connected future that transcends borders and boundaries.
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Let’s talk through some of the biggest challenges around transforming into a data-driven communications organization (and how the Data Intelligence Platform addresses them):
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Improving the Customer Experience
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An organization's ability to deliver 1:1 personalization at scale goes a long way to meeting customers where they’re at, effectively mitigating churn. Unfortunately, legacy technologies are complex to manage and costly to scale for today’s massive volumes of customer data. AI and personalization at scale is impossible when you have fragmented views of an audience, lack real-time capabilities, and struggle to make the leap from descriptive to predictive analytics.
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The Advantages of a Data Intelligence Platform: The Data Intelligence Platform for Communications enables teams to have a relationship with customers on their terms: a single, unified data platform where teams can perform the analysis needed to better understand sentiment across channels, create and deliver personalized recommendations, all with a robust ecosystem of data partners to deliver dynamic engagements in real-time that improve customer experience, increase profitability, and reduce churn.
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Reducing the Cost to Serve/Operate
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Complexity has driven increased costs across the board, which presents a twofold challenge. On one hand, the rapid pace of innovation requires constant upgrades and investments in new technologies. This results in higher initial capital expenditures and ongoing operational costs to remain at the forefront of technological advancements. On the other hand, legacy systems and outdated infrastructure can also be cost-intensive to maintain and integrate with newer technologies. The need for seamless interoperability between legacy and modern systems demands substantial resources, driving up operational expenses.
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Additionally, the demand for seamless, high-quality customer experiences introduces cost pressures. As customers expect personalized, real-time services, organizations must invest in sophisticated customer relationship management (CRM) systems, data analytics tools, and AI-driven automation to provide tailored solutions. These investments, while enhancing customer satisfaction, can strain budgets and resources, especially if not carefully managed. Moreover, the necessity of robust cybersecurity measures to safeguard sensitive data against increasing cyber threats contributes to the escalating operational costs, requiring continuous investments in cybersecurity tools, personnel training, and risk mitigation strategies.
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The Advantages of a Data Intelligence Platform: With data and AI on the same unified platform, teams can perform more intelligent network optimization and predictive maintenance, deploy robotic process automation, and push compute and AI to edge networks to reduce spend, save network bandwidth, and generate incremental revenue. Only a Data Intelligence Platform combines the unified data and governance benefits of a Data Lakehouse with the capabilities of generative AI.
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Identifying New Revenue Sources
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As traditional revenue streams such as voice and messaging face increased competition from new entrants, mobile virtual network operators (MVNO) and evolving customer preferences, organizations need to consider how diversification can mitigate risk. To address this challenge, teams must strategically leverage data and AI-driven insights to uncover untapped opportunities, anticipate market trends, and create innovative services that resonate with their customer base.
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Here, data emerges as a valuable asset. With no shortage of customer data, network performance metrics, and usage patterns, organizations can leverage advanced analytics and AI to extract actionable insights that help teams better understand customer behavior, preferences, and pain points. This data-driven approach empowers teams to out-maneuver competition in an increasingly dynamic environment.
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The Advantages of a Data Intelligence Platform on Azure: Built AI-first, the Databricks Data Intelligence Platform on Azure empowers organizations to tap the full potential of AI/ML workloads to forecast market trends, predict demand patterns, and simulate the impact of different business strategies. This empowers teams to make better-informed decisions on where to invest resources and which new revenue avenues to explore. In addition, the Data Intelligence Platform for Communications makes data sharing a first-class citizen within your enterprise, allowing organizations to share and monetize their data as a product. Tight integration with Microsoft Azure, means that Databricks' own Gen AI capabilities work seamlessly with leading Azure AI capabilities, including Azure Open AI.
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Achieving Scale and Security
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Striking a delicate balance between achieving profitable scale and ensuring robust security has become a multifaceted challenge. As communication service providers scale their networks and invest in cutting-edge technologies, they are met with the imperative to safeguard these investments against an increasingly sophisticated array of cyber threats. Simultaneously, the pressure to generate revenue while maintaining operational efficiency requires extracting more value from data and AI investments to optimize network performance, enhance customer experiences, and streamline operations.
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The Advantages of a Data Intelligence Platform: Only Azure Databricks provides a single, unified data platform where data combines with the full potential of AI. Whether predicting network congestion, allocating resources efficiently, or optimizing bandwidth usage, teams building atop a Data Intelligence Platform can more easily achieve cost-effective scale without compromising quality of service.
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Go from idea to proof-of-concept in weeks with pre-built solution accelerators
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Built on top of our Data Intelligence Platform on Azure, Azure Databricks and our ecosystem of partners offer packaged solution accelerators to help organizations tackle the most common and high-value use cases in the industry. We’ve built a number of communications-specific accelerators that include:
Telco Network Analytics: Increase network reliability for the 5G+ era and reduce customer churn with robust pipelines and accurate forecasting
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Customer Entity Resolution: Data generated through transactions, support center calls, and more can come together to form a 360-degree view of your customers
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Behavioral Segmentation: Create advanced segments to drive better purchasing predictions based on behaviors
Recommendation Engines: Increase conversions and engagement with personalized omnichannel recommendations
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Video Quality of Experience: Analyze batch and streaming data to ensure a performant content experience for streaming services
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A growing partner ecosystem
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Azure Databricks is working with industry-leading consulting and technology partners to enable best-in-class solutions. Azure Databricks helps customers across the communications industry ecosystem to reduce operational costs and improve customer engagement at a global scale. Azure Databricks has hundreds of joint Lakehouse customers, including T-Mobile, which uses Azure Databricks to more accurately determine construction readiness, ensure timely procurement of cell-site equipment, and identify fraud and waste of network materials; and AT&T, who uses the Databricks Data Intelligence Platform on Azure to protect its customer from fraud and increase operational efficiencies, benefiting both customers and the business.
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Databricks Communications Implementation Partners: Databricks has also partnered with system integrators to deliver scalable industry solutions that help customers more rapidly address common use cases. Communications partners include Accenture, Amdocs, Capgemini, Slalom, and Tredence who have all worked with communications customers to help them enable the next generation of big data and AI use cases for communications leaders across the globe. Tailor-made for communication use cases, featured partner solutions include:
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Accenture is investing in unique and differentiating telecommunications assets and accelerators built on Databricks that help their clients realize value faster. One of their largest projects was at a large global telecom, helping to build their enterprise data and AI foundation on Databricks. By implementing the Databricks Intelligence Platform and connecting their business, network, and operational data with Unity Catalog, the client has been able to accelerate ML and generative AI use cases that reduce churn, optimize 5G deployment, and accelerate their customer experience transformation.
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Amdocs for Data Transformation: Leveraging the Amdocs Logical Data Model -- a TM Forum-certified communications-specific data model, which is optimized for modern technologies and near real-time processing -- Amdocs delivers an event-driven, scalable, consumption-ready data integration layer to help communications leaders with decision-making and creating more personalized customer experiences.
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Tredence Telco.Atom.ai: An integrated accelerator ecosystem consisting of telecommunications-specific data models, pipelines, AI/ML code notebooks, front-end consumption layers, and a robust MLOps process, which allows telcos to develop and scale AI applications 50% faster.
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“Generative AI has brought data to the forefront of discussions even among executives outside the data space. The ease of use and increasing value of generative AI applications have made data and AI more accessible to business-focused leaders. This convergence of art and science in creative processes, such as AI-driven content creation, marks an exciting development in the industry.”
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Manish Dasaur, Chief Data and Analytics Officer, Comms and Media, North America, Accenture
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“The telecommunications industry is in the midst of major transformation, driven by factors like 5G (with 6G on the horizon) and next-generation networks, convergence with other industries, and shifting customer expectations. Capgemini has successfully implemented Databricks architecture for our telecommunication clients, facilitating data-driven decisions across customer care, network, field operations, and many more business domains. Lakehouse architecture can play a pivotal role in building a highly scalable data and analytics platform to unlock significant value, perform comprehensive network coverage analysis, improve customer experience, and adapt to ever-changing telecommunications landscape.”
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Pankaj Kaul, Insights and Data Leader (Telecommunication, Media, Technology, and Digital), Capgemini
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Databricks Communications Technology Partners: Our technology partners are critical to success and augment Databricks with industry-specific capability. Communications customers are leveraging Azure Databricks technology partners as they look to improve their consumer, network and employee experiences and deliver advanced analytics and machine learning solutions.
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Want to learn more about the Databricks Data Intelligence Platform on Azure for Communications? Click here for our solutions page. We’re thrilled to continue to invest in the Communications industry, empowering leaders put data, AI and analytics at the very center of their organization.
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This post is authored in conjunction with Bryan Saftler, Global Head of Marketing for Communications, Media & Entertainment at Databricks and Steve Sobel, Global Head - Communications, Media & Entertainment GTM at Databricks.
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The communications industry is undergoing one of the most significant periods of growth (and change) in its 100+ year history. The dramatic increase in global traffic, the customer expectation for enhanced services, and the need for more network equipment is driving more complex and costly network management. In addition, data shows that as customers demand higher quality service and better customer experiences (CX), they’re more likely to churn when their needs are not met.
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As a result, Communications Service Providers (CSPs) are looking to data and AI use cases to help reduce costs to serve and operate, develop and maintain great customer experiences, identify opportunities for revenue growth, and achieve scale with secure and reliable services. No small feat.
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To illustrate this, look no further than the explosion of digital technologies — such as 5G, IoT, edge computing, and AI — which has ushered in a new era of big data. For example, according to Cisco's Visual Networking Index (VNI) Global Mobile Data Traffic Forecast, global mobile data traffic has grown to 77.5 exabytes per month. This growth is driven by the proliferation of mobile devices and the increasing demand for data-intensive applications. In addition, the number of connected IoT devices is skyrocketing. According to Statista, the number of connected IoT devices is expected to reach 31 billion by 2025, generating approximately 79.4 zettabytes of data annually. This data, while large and unwieldy, is critical to building a virtuous loop between networks and customers. By bringing this data together, CSPs can better understand the factors that contribute to a positive or negative customer experience.
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To make this virtuous loop effective, the key is making sure that the right humans have access to the right data at the right moment in time. The need for a modern and unified data analytics and AI platform has never been greater. The problem? Traditional data architectures weren’t built to support Generative AI and machine learning use cases, especially across broad teams of data engineers, data scientists and analysts, while supporting the scale and agility communications companies need to handle evolving customer demands. This has led to heavy investments in modern data technologies and industry partnerships to use data more thoughtfully. This is achieved by:
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Having a single view of all data in a unified architecture, including unstructured data like video, images and voice content.
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Ensuring data is in a ready state for all analytics, AI, and ML use cases
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Having a cloud infrastructure environment based on open source and open standards so IT and data teams can move with agility.
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In a nutshell, ensuring all of your data is AI and business intelligence (BI) ready and being able to move fast to stay ahead of consumer and employee expectations is a critical strategy for every communications organization.
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Introducing the Databricks Data Intelligence Platform on Azure for Communications
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On Tuesday January 9th, we announced the world’s first Data Intelligence Platform with enhanced capabilities for the Communications industry for Databricks, including Azure Databricks. Built atop our Lakehouse architecture, the Data Intelligence Platform combines all the best features of a Data Lakehouse with generative AI capabilities. This means an open, unified foundation for all your data along with unprecedented access to analytics and AI across your organization.
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We built the Databricks Data Intelligence Platform to help organizations better succeed with AI, democratize insights, and drive down costs. Teams can develop generative AI applications on their data without sacrificing data privacy or confidential IP. More humans across the organization can discover insights from more data in the language of their business. And teams can gain efficiency and simplify complexity by unifying data, governance, and AI together. This is only possible on a Data Intelligence Platform.
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Databricks stands as a strategic partner for communications organizations. By leveraging the power of the Databricks Data Intelligence Platform, CSPs can gain a holistic view of their networks, operations, and customer interactions like never before. This newfound data-driven intelligence allows them to optimize network performance, predict and proactively address service disruptions, and deliver highly personalized customer experiences that drive loyalty and satisfaction. As data-driven enterprises, CSPs will be able to lead with innovation, deliver unmatched customer experiences, and pave the way for a connected future that transcends borders and boundaries.
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Let’s talk through some of the biggest challenges around transforming into a data-driven communications organization (and how the Data Intelligence Platform addresses them):
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Improving the Customer Experience
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An organization's ability to deliver 1:1 personalization at scale goes a long way to meeting customers where they’re at, effectively mitigating churn. Unfortunately, legacy technologies are complex to manage and costly to scale for today’s massive volumes of customer data. AI and personalization at scale is impossible when you have fragmented views of an audience, lack real-time capabilities, and struggle to make the leap from descriptive to predictive analytics.
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The Advantages of a Data Intelligence Platform: The Data Intelligence Platform for Communications enables teams to have a relationship with customers on their terms: a single, unified data platform where teams can perform the analysis needed to better understand sentiment across channels, create and deliver personalized recommendations, all with a robust ecosystem of data partners to deliver dynamic engagements in real-time that improve customer experience, increase profitability, and reduce churn.
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Reducing the Cost to Serve/Operate
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Complexity has driven increased costs across the board, which presents a twofold challenge. On one hand, the rapid pace of innovation requires constant upgrades and investments in new technologies. This results in higher initial capital expenditures and ongoing operational costs to remain at the forefront of technological advancements. On the other hand, legacy systems and outdated infrastructure can also be cost-intensive to maintain and integrate with newer technologies. The need for seamless interoperability between legacy and modern systems demands substantial resources, driving up operational expenses.
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Additionally, the demand for seamless, high-quality customer experiences introduces cost pressures. As customers expect personalized, real-time services, organizations must invest in sophisticated customer relationship management (CRM) systems, data analytics tools, and AI-driven automation to provide tailored solutions. These investments, while enhancing customer satisfaction, can strain budgets and resources, especially if not carefully managed. Moreover, the necessity of robust cybersecurity measures to safeguard sensitive data against increasing cyber threats contributes to the escalating operational costs, requiring continuous investments in cybersecurity tools, personnel training, and risk mitigation strategies.
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The Advantages of a Data Intelligence Platform: With data and AI on the same unified platform, teams can perform more intelligent network optimization and predictive maintenance, deploy robotic process automation, and push compute and AI to edge networks to reduce spend, save network bandwidth, and generate incremental revenue. Only a Data Intelligence Platform combines the unified data and governance benefits of a Data Lakehouse with the capabilities of generative AI.
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Identifying New Revenue Sources
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As traditional revenue streams such as voice and messaging face increased competition from new entrants, mobile virtual network operators (MVNO) and evolving customer preferences, organizations need to consider how diversification can mitigate risk. To address this challenge, teams must strategically leverage data and AI-driven insights to uncover untapped opportunities, anticipate market trends, and create innovative services that resonate with their customer base.
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Here, data emerges as a valuable asset. With no shortage of customer data, network performance metrics, and usage patterns, organizations can leverage advanced analytics and AI to extract actionable insights that help teams better understand customer behavior, preferences, and pain points. This data-driven approach empowers teams to out-maneuver competition in an increasingly dynamic environment.
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The Advantages of a Data Intelligence Platform on Azure: Built AI-first, the Databricks Data Intelligence Platform on Azure empowers organizations to tap the full potential of AI/ML workloads to forecast market trends, predict demand patterns, and simulate the impact of different business strategies. This empowers teams to make better-informed decisions on where to invest resources and which new revenue avenues to explore. In addition, the Data Intelligence Platform for Communications makes data sharing a first-class citizen within your enterprise, allowing organizations to share and monetize their data as a product. Tight integration with Microsoft Azure, means that Databricks' own Gen AI capabilities work seamlessly with leading Azure AI capabilities, including Azure Open AI.
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Achieving Scale and Security
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Striking a delicate balance between achieving profitable scale and ensuring robust security has become a multifaceted challenge. As communication service providers scale their networks and invest in cutting-edge technologies, they are met with the imperative to safeguard these investments against an increasingly sophisticated array of cyber threats. Simultaneously, the pressure to generate revenue while maintaining operational efficiency requires extracting more value from data and AI investments to optimize network performance, enhance customer experiences, and streamline operations.
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The Advantages of a Data Intelligence Platform: Only Azure Databricks provides a single, unified data platform where data combines with the full potential of AI. Whether predicting network congestion, allocating resources efficiently, or optimizing bandwidth usage, teams building atop a Data Intelligence Platform can more easily achieve cost-effective scale without compromising quality of service.
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Go from idea to proof-of-concept in weeks with pre-built solution accelerators
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Built on top of our Data Intelligence Platform on Azure, Azure Databricks and our ecosystem of partners offer packaged solution accelerators to help organizations tackle the most common and high-value use cases in the industry. We’ve built a number of communications-specific accelerators that include:
Telco Network Analytics: Increase network reliability for the 5G+ era and reduce customer churn with robust pipelines and accurate forecasting
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Customer Entity Resolution: Data generated through transactions, support center calls, and more can come together to form a 360-degree view of your customers
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Behavioral Segmentation: Create advanced segments to drive better purchasing predictions based on behaviors
Recommendation Engines: Increase conversions and engagement with personalized omnichannel recommendations
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Video Quality of Experience: Analyze batch and streaming data to ensure a performant content experience for streaming services
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A growing partner ecosystem
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Azure Databricks is working with industry-leading consulting and technology partners to enable best-in-class solutions. Azure Databricks helps customers across the communications industry ecosystem to reduce operational costs and improve customer engagement at a global scale. Azure Databricks has hundreds of joint Lakehouse customers, including T-Mobile, which uses Azure Databricks to more accurately determine construction readiness, ensure timely procurement of cell-site equipment, and identify fraud and waste of network materials; and AT&T, who uses the Databricks Data Intelligence Platform on Azure to protect its customer from fraud and increase operational efficiencies, benefiting both customers and the business.
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Databricks Communications Implementation Partners: Databricks has also partnered with system integrators to deliver scalable industry solutions that help customers more rapidly address common use cases. Communications partners include Accenture, Amdocs, Capgemini, Slalom, and Tredence who have all worked with communications customers to help them enable the next generation of big data and AI use cases for communications leaders across the globe. Tailor-made for communication use cases, featured partner solutions include:
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Accenture is investing in unique and differentiating telecommunications assets and accelerators built on Databricks that help their clients realize value faster. One of their largest projects was at a large global telecom, helping to build their enterprise data and AI foundation on Databricks. By implementing the Databricks Intelligence Platform and connecting their business, network, and operational data with Unity Catalog, the client has been able to accelerate ML and generative AI use cases that reduce churn, optimize 5G deployment, and accelerate their customer experience transformation.
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Amdocs for Data Transformation: Leveraging the Amdocs Logical Data Model -- a TM Forum-certified communications-specific data model, which is optimized for modern technologies and near real-time processing -- Amdocs delivers an event-driven, scalable, consumption-ready data integration layer to help communications leaders with decision-making and creating more personalized customer experiences.
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Tredence Telco.Atom.ai: An integrated accelerator ecosystem consisting of telecommunications-specific data models, pipelines, AI/ML code notebooks, front-end consumption layers, and a robust MLOps process, which allows telcos to develop and scale AI applications 50% faster.
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“Generative AI has brought data to the forefront of discussions even among executives outside the data space. The ease of use and increasing value of generative AI applications have made data and AI more accessible to business-focused leaders. This convergence of art and science in creative processes, such as AI-driven content creation, marks an exciting development in the industry.”
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Manish Dasaur, Chief Data and Analytics Officer, Comms and Media, North America, Accenture
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“The telecommunications industry is in the midst of major transformation, driven by factors like 5G (with 6G on the horizon) and next-generation networks, convergence with other industries, and shifting customer expectations. Capgemini has successfully implemented Databricks architecture for our telecommunication clients, facilitating data-driven decisions across customer care, network, field operations, and many more business domains. Lakehouse architecture can play a pivotal role in building a highly scalable data and analytics platform to unlock significant value, perform comprehensive network coverage analysis, improve customer experience, and adapt to ever-changing telecommunications landscape.”
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Pankaj Kaul, Insights and Data Leader (Telecommunication, Media, Technology, and Digital), Capgemini
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Databricks Communications Technology Partners: Our technology partners are critical to success and augment Databricks with industry-specific capability. Communications customers are leveraging Azure Databricks technology partners as they look to improve their consumer, network and employee experiences and deliver advanced analytics and machine learning solutions.
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Want to learn more about the Databricks Data Intelligence Platform on Azure for Communications? Click here for our solutions page. We’re thrilled to continue to invest in the Communications industry, empowering leaders put data, AI and analytics at the very center of their organization.
Powering the data and AI-driven future of the Communications Industry with the
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