Embedded Business Intelligence- A Guide to an Upgraded BI

Embedded Business Intelligence- A Guide to an Upgraded BI

Businesses are becoming more data-driven, and the potential to use data and analytics to differentiate market leaders is becoming increasingly important. Customers are demanding actionable insights into the apps, products, and services they use daily, and businesses of all sizes are trying to meet these demands.


Product managers understand they must provide their consumers with concrete insights derived from processed data. However, creating these features from scratch can sometimes be a difficult task. The answer is simple: add an analytics platform into your core product, like integrated business intelligence.

Embedding an analytics system may also help a company get more value out of the data it has already spent time acquiring, keeping, and analyzing. Embedded business intelligence is among the most important use cases in the broader data analytics sector, as companies leverage the technology to build extranet apps and give analytics as part of a larger business application. Those looking to integrate analytics tools into their existing business operations must prioritize their requirements in order of importance.

Why Should Businesses Choose Embedded Business Intelligence?

Embedded business intelligence (Embedded BI) is the future of BI, because it makes it easy for your employees to use dashboards and make data-based decisions as they go about their work. Let's look at some of the reasons why you should opt for embedded business intelligence.

Insightful Decision-Making

Embedding BI allows you to leverage insights, making data more accessible irrespective of technical skills. Embedded analytics tools provide you with quick access to data that can help you make better business decisions.

If “glitches” show up on the radar, strategic decision-makers can raise the alarm, assess the threat, develop remedies, and come up with solutions, and change the business course.

Create an Effortless Workflow

According to MarTech Today and Blissfully, "businesses with fewer than 50 employees have approximately 40 applications in total." The truth is that current employee operations are complicated and scattered across several platforms. BI platforms aren't a silver bullet for this challenge. Embedded BI, on the other hand, can be beneficial.

Embedded BI eliminates the need for your sales executive to make choices and streamlines their workflow. It seamlessly integrates the data into this team's existing tool process with minimal disruption.

Reduce your Reliance on Developers

Businesses that depend entirely on their overburdened developers to implement an analytics solution will invariably create a data bottleneck. Embedded BI tools reduce this barrier and encourages everyone who works with embedded data to be more flexible and iterative.

With the help of embedded business intelligence, you can check and analyze business data and adjust visuals on the go by utilizing dynamic data visualization. Drill-down, filtering, and search are interaction options available on these embedded BI tools, allowing to freely explore reports and dashboards and extract crucial business insights.

Should You Build In-House Embedded BI or Buy a Third-Party?

When it comes to deploying an embedded BI tool, you have two options. Organizations can either develop their products in-house or buy them from a third party. Building an embedded BI platform from scratch might take a long time and may be costly like most businesses with software as their key competence, general companies should first explore commercially available embedded BI solutions. Also, purchasing embedded BI allows businesses to focus on their core competencies while leveraging the tools to deliver embedded BI features to users faster.

Top Embedded Business Intelligence Tools for C-Suite (Include cases)

Many embedded BI tools are available in the market but choosing the most appropriate tool from among them is a major task. So, to end your search for the perfect embedded BI tool, you can check out the list below. We have also included case studies of these embedded business intelligence applications for you to make a better decision.

Sisense BI Helps Crunchbase Get Access to the Right Data across the Organization

In the business world, Crunchbase is the most important database, and they needed a powerful platform to get all their data together, so they went with Sisense BI.

Crunchbase was able to take its analytics to the next level using Sisense for Cloud Data Teams, which allowed them to access their data, from their marketing stack to Salesforce platforms to website impression data, to create a holistic view of their business and customers.

It's also good for Crunchbase's marketing team because the interface of Sisense is easy to use. This makes it easy for business users to understand data on their own and use it for decision making.

Microsoft Power BI Helps Heathrow Airport in Making Travels Less Stressful

Heathrow Airport serves as the U.K.'s international gateway. Heathrow Airport serves 80 million passengers each day, and the airport is utilizing Microsoft Power BI and Microsoft Azure to make travel less stressful for travelers. With the help of Power BI, Heathrow Airport gets real-time operational data for its employees. It enables to assist passengers in navigating the airport despite bad weather, canceled flights, and other delays.

For example, a disturbance in the jet stream caused a delay of 20 flights, resulting in 6,000 more passengers arriving at the airport at 6:00 p.m. Previously, employees at immigration, customs, luggage handling, and food services would not be aware of the unexpected passengers until they arrived, forcing them to make do with what they had. But now, all these employees are notified one to two hours prior so that they can arrange extra workers, buses, food, and other resources to assist with the inflow.

Qlik Sense Helps Tesla Users Get Information About Tesla SuperCharge Stations

Tesla customers use a Qlik Sense application to track the locations of Tesla supercharger stations and obtain information about them. The software uses real-world road network computations and overlap predictions based on Tesla vehicles' typical battery range. This app needs to work with Qlik GeoAnalytics because it displays supercharging stations on a map.

Charger status is also displayed on the dashboard. You can make choices based on where you are on the dashboard, and the program will respond based on the associations between data sets.

Closing Lines

Embedded business intelligence has significant potential for small firms and enterprise powerhouses alike.

Embedded analytics outperforms previous solutions in extracting the most value from your data and enabling today's crucial business choices. However, long-term use of embedded analytics will require a significant amount of work on the part of the C-suite. The C-suite will have a positive influence and assure continued analytics success by applying predictive analytics, integrating machine learning, and encouraging a data-driven culture.


FAQ


Is there a limit to embedding analytics into existing applications?

Embedded BI products have less limitations than independent tools and are mostly more capable. Machine learning, NLP, and artificial intelligence (AI) are included in the current, more modern generation of embedded systems, although these abilities are generally not included in standalone solutions.

What should purchasers keep in mind while selecting a vendor?

Users who have only used a typical BI or data analytics tool should be wary of colorful charts and data visualizations. Buyers must think about the long term, particularly when it comes to product maintenance, making changes across instances, and offering a simple yet tailored experience to the end-user.

Are embedded business intelligence solutions easy to set up?

The beauty of embedded analytics and BI solutions is quick and simple to deploy. You can either add them to an existing system or design a new one based on your requirements.

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Etiya

Etiya is the leading Independent Software Vendor providing comprehensive Telco CRM, Catalog-Driven B/OSS, Social CRM, and Big Data Analytics to Communication & Digital Service Providers. With its award-winning innovative products, rapid deployments, and end-to-end implementation capabilities, Etiya provides the most complete offer in the market. Etiya is a nominee for TM Forum’s Outstanding Contribution to Enabling Improved Business Agility Award 2016 and the winner of the TM Forum Excellence Award for Customer Centricity 2015.

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In partnership, EAGLYS, Inc., Mitsui & Co., Ltd., and Quantinuum have integrated Quantum Origin into EAGLYS' secure computation product DataArmor, strengthening the platform against the quantum threat to encrypted data. Mitsui and EAGLYS have used secure computation technology to build a platform that allows research institutes and businesses to securely collaborate using each other's data and AI models. DataArmor uniquely maintains the confidentiality and security of sensitive data and AI models using homomorphic encryption, a technology that allows analysis to be performed on data while still encrypted. This protects encrypted data from being revealed when shared, safeguarding organizations and their Intellectual Property against advanced cyber threats. EAGLYS has now integrated Quantum Origin, the world's only solution that uses the power of quantum computing processes to provably strengthen encryption keys, as part of their Quantum-Resistant Data Analytics (AI) Platform. 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SingleStore | January 25, 2024

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data.world | January 24, 2024

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EAGLYS, Mitsui and Quantinuum Collaborate to Build a Quantum-Resistant Data Analytics (AI) Platform Using Quantum Computing Hardened Encryption Keys

Mitsui & Co., Ltd | December 13, 2023

In partnership, EAGLYS, Inc., Mitsui & Co., Ltd., and Quantinuum have integrated Quantum Origin into EAGLYS' secure computation product DataArmor, strengthening the platform against the quantum threat to encrypted data. Mitsui and EAGLYS have used secure computation technology to build a platform that allows research institutes and businesses to securely collaborate using each other's data and AI models. DataArmor uniquely maintains the confidentiality and security of sensitive data and AI models using homomorphic encryption, a technology that allows analysis to be performed on data while still encrypted. This protects encrypted data from being revealed when shared, safeguarding organizations and their Intellectual Property against advanced cyber threats. EAGLYS has now integrated Quantum Origin, the world's only solution that uses the power of quantum computing processes to provably strengthen encryption keys, as part of their Quantum-Resistant Data Analytics (AI) Platform. This integration strengthens the resilience of DataArmor against the threat of a quantum-computing-based attack. Quantum computers are expected to empower significant innovation in the future and create approximately 100 trillion yen in value by 20351. At the same time, the development of quantum computing technology presents a new threat to the cryptographic security measures that protect the confidentiality of encrypted data and communications. RSA, one of the most widely used cryptographic algorithms, may soon be deciphered by cybercriminals to expose confidential data. It is unclear when a quantum computer will be capable of cracking existing encryption, but organizations are increasingly concerned about cyber security attacks called 'Hack now, Decrypt later.' A recent Deloitte survey revealed that over 50%2 of cyber professionals believe their organization is at risk from this attack, where malicious third parties steal and store encrypted data to decrypt it when the quantum computing technology is available. As a countermeasure against such potential threats, organizations must strengthen encryption protection for data and AI models by using post-quantum cryptographic algorithms and hardening cryptographic keys. Research institutes and businesses increasingly need to collaborate using each other's data and AI models to accelerate innovation in chemical materials development, drug discovery, financial analysis, and retail trends. To maintain the confidentiality and security of the data and AI models used in these collaborations, EAGLYS' DataArmor platform combines fully homomorphic encryption based on lattice cryptography and Quantum Origin's quantum-derived entropy for key generation to strengthen protection against a quantum computing based attack. Going forward, the three companies will continue to develop new use cases utilizing this platform. "We are pleased to collaborate on this advanced project with Quantinuum, a world-class quantum computing company, and our valued partner Mitsui & Co. This collaboration is an important initiative for our business and will enhance our Homomorphic Encryption platform, enabling us to create new value for our customers through AI and data in a highly secure environment. By deploying the Quantum-Resilient AI Platform together with the three companies, we hope to further increase customer value through secure data sharing and AI in the chemical, medical, financial, and retail industries.", said Hiroki Imabayashi, Founder and CEO, EAGLYS Inc. "Through this collaboration, we are able to present a quantum-resistant data analytics (AI) platform capable of creating new value using EAGLYS' secure computation technology. We are convinced that by combining EAGLYS' secure computation technology with Quantum Origin, DataArmor will become an increasingly important solution to prepare for potential threats that may accompany the commercialization of quantum computers. We will continue collaborating with both companies and focus on realizing new customer value by combining Secure Computation and Quantum Technology." said Koji Naniwada, Deputy General Manager & Senior Tech Lead, Quantum Innovation Dept., Corporate Development Div., Mitsui & Co., Ltd. Duncan Jones, Head of Cybersecurity, Quantinuum, added, "Hardening encryption keys is critical to protecting sensitive data in the post-quantum era, and Quantum Origin is the world's only technology that provably strengthens key generation. By integrating Quantum Origin, EAGLYS is future-proofing the security and integrity of its customer's data." About Quantinuum Quantinuum is one of the world's largest integrated quantum computing companies, formed by the combination of Honeywell Quantum Solutions' world-leading hardware and Cambridge Quantum's class-leading middleware and applications. Quantinuum accelerates quantum computing and the development of applications across chemistry, cybersecurity, finance, and optimization. The company employs over 480 individuals, including 350 scientists, at nine sites across the United States, Europe, and Japan. About Mitsui & Co., Ltd. Mitsui & Co. is a global trading and investment company with a presence in more than 60 countries and a diverse business portfolio covering a wide range of industries. The company identifies, develops, and grows its businesses in partnership with a global network of trusted partners including world leading companies, combining its geographic and cross-industry strengths to create long-term sustainable value for its stakeholders. Mitsui has set three key strategic initiatives for its current Medium-term Management Plan: supporting industries to grow and evolve with stable supplies of resources and materials, and providing infrastructure; promoting a global transition to low-carbon and renewable energy; and empowering people to lead healthy lives through the delivery of quality healthcare and access to good nutrition. About EAGLYS Inc EAGLYS is a company that provides an AI platform that uses AI and Homomorphic Encryption. The company creates new value by collaborating data from various industries such as chemical, manufacturing, medical, and retail. Particularly in the field of chemistry, EAGLYS provides solutions that significantly change industry practices.

Read More

Data Architecture

SingleStore Announces Real-time Data Platform to Further Accelerate AI, Analytics and Application Development

SingleStore | January 25, 2024

SingleStore, the database that allows you to transact, analyze and contextualize data, today announced powerful new capabilities — making it the industry’s only real-time data platform. With its latest release, dubbed SingleStore Pro Max, the company announced ground-breaking features like indexed vector search, an on-demand compute service for GPUs/ CPUs and a new free shared tier, among several other innovative new products. Together, these capabilities shrink development cycles while providing the performance and scale that customers need for building applications. In an explosive generative AI landscape, companies are looking for a modern data platform that’s ready for enterprise AI use cases — one with best-available tooling to accelerate development, simultaneously allowing them to marry structured or semi-structured data residing in enterprise systems with unstructured data lying in data lakes. “We believe that a data platform should both create new revenue streams while also decreasing technological costs and complexity for customers. And this can only happen with simplicity at the core,” said Raj Verma, CEO, SingleStore. “This isn’t just a product update, it’s a quantum leap… SingleStore is offering truly transformative capabilities in a single platform for customers to build all kinds of real-time applications, AI or otherwise.” “At Adobe, we aim to change the world through digital experiences,” said Matt Newman, Principal Data Architect, Adobe. “SingleStore’s latest release is exciting as it pushes what is possible when it comes to database technology, real-time analytics and building modern applications that support AI workloads. We’re looking forward to these new features as more and more of our customers are seeking ways to take full advantage of generative Al capabilities.” Key new features launched include: Indexed vector search. SingleStore has announced support for vector search using Approximate Nearest Neighbor (ANN) vector indexing algorithms, leading to 800-1,000x faster vector search performance than precise methods (KNN). With both full-text and indexed vector search capabilities, SingleStore offers developers true hybrid search that takes advantage of the full power of SQL for queries, joins, filters and aggregations. These capabilities firmly place SingleStore above vector-only databases that require niche query languages and are not designed to meet enterprise security and resiliency needs. Free shared tier. SingleStore has announced a new cloud-based Free Shared Tier that’s designed for startups and developers to quickly bring their ideas to life — without the need to commit to a paid plan. On-demand compute service for GPUs and CPUs. SingleStore announces a compute service that works alongside SingleStore’s native Notebooks to let developers spin up GPUs and CPUs to run database-adjacent workloads including data preparation, ETL, third-party native application frameworks, etc. This capability brings compute to algorithms, rather than the other way around, enabling developers to build highly performant AI applications safely and securely using SingleStore — without unnecessary data movement. New CDC capabilities for data ingest and egress. To ease the burden and costs of moving data in and out of SingleStore, SingleStore is adding native capabilities for real-time Change Data Capture (CDC) in for MongoDB®, MySQL and ingestion from Apache Iceberg without requiring other third party CDC tools. SingleStore will also support CDC out capabilities that ease migrations and enable the use of SingleStore as a source for other applications and databases like data warehouses and lakehouses. SingleStore Kai™. Now generally available, and ready for both analytical and transactional processing for apps originally built on MongoDB. Announced in public preview in early 2023, SingleStore Kai is an API to deliver over 100x faster analytics on MongoDB® with no query changes or data transformations required. Today, SingleStore Kai supports BSON data format natively, has improved transactional performance, increased performance for arrays and offers industry-leading compatibility with MongoDB query language. Projections: To further advance as the world’s fastest HTAP database, SingleStore has added Projections. Projections allow developers to greatly speed up range filters and group by operations by introducing secondary sort and shard keys. Query performance improvements range from 2-3x or more, depending on the size of the table. With this latest release, SingleStore becomes the industry’s first and only real-time data platform designed for all applications, analytics and AI. SingleStore supports high-throughput ingest performance, ACID transactions and low-latency analytics; and structured, semi-structured (JSON, BSON, text) and unstructured data (vector embeddings of audio, video, images, PDFs, etc.). Finally, SingleStore’s data platform is designed not just with developers in mind, but also ML engineers, data engineers and data scientists. “Our new features and capabilities advance SingleStore’s mission of offering a real-time data platform for the next wave of gen AI and data applications,” said Nadeem Asghar, SVP, Product Management + Strategy at SingleStore. “New features, including vector search, Projections, Apache Iceberg, Scheduled Notebooks, autoscaling, GPU compute services, SingleStore Kai™, and the Free Shared Tier allow startups — as well as global enterprises — to quickly build and scale enterprise-grade real-time AI applications. We make data integration with third-party databases easy with both CDC in and CDC out support.” "Although generative AI, LLM, and vector search capabilities are early stage, they promise to deliver a richer data experience with translytical architecture," states the 2023 report, “Translytical Architecture 2.0 Evolves To Support Distributed, Multimodel, And AI Capabilities,” authored by Noel Yuhanna, Vice President and Principal Analyst at Forrester Research. "Generative AI and LLM can help democratize data through natural language query (NLQ), offering a ChatGPT-like interface. Also, vector storage and index can be leveraged to perform similarity searches to support data intelligence." SingleStore has been on a fast track leading innovation around generative AI. The company’s product evolution has been accompanied by high-momentum growth in customers and surpassing $100M in ARR late last year. SingleStore also recently ranked #2 in the emerging category of vector databases, and was recognized by TrustRadius as a top vector database in 2023. Finally, SingleStore was a winner of InfoWorld’s Technology of the year in the database category. To learn more about SingleStore visit here. About SingleStore SingleStore empowers the world’s leading organizations to build and scale modern applications using the only database that allows you to transact, analyze and contextualize data in real time. With streaming data ingestion, support for both transactions and analytics, horizontal scalability and hybrid vector search capabilities, SingleStore helps deliver 10-100x better performance at 1/3 the costs compared to legacy architectures. Hundreds of customers worldwide — including Fortune 500 companies and global data leaders — use SingleStore to power real-time applications and analytics. Learn more at singlestore.com. Follow us @SingleStoreDB on Twitter or visit www.singlestore.com.

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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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