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Amazon
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Amazon Redshift Serverless adds higher base capacity of up to 1024 RPUs
- Amazon Redshift Serverless is a pay-per-use serverless data warehousing service that eliminates the need for manual cluster provisioning and management.
- The key innovation of Redshift Serverless is its ability to automatically scale compute up or down based on your workload demands, maintaining optimal performance and cost-efficiency without manual intervention.
- Redshift Serverless now has a default 128 RPUs, capable of analyzing petabytes of data and can be scaled up to 10 times the base capacity.
- In this post, we explore the new higher base capacity of 1024 RPUs in Redshift Serverless, which doubles the previous maximum of 512 RPUs.
- The need for 1024 RPUs is driven by the increasing integration of data warehouses with data lakes and other distributed data sources, that add to the overall computational burden.
- The 1024 RPU configuration delivers the necessary performance to meet demanding service level agreements (SLAs) and provide timely data availability for downstream business intelligence and decision-making processes.
- The 1024 RPU configuration can significantly improve query completion times, queries performing faster, resulting in faster connections ending.
- Redshift Serverless offers a price-performance target that balances performance and cost to meet your organization’s unique data warehousing needs.
- Organizations should evaluate their current data warehousing needs and consider running a proof of concept with the 1024 RPU configuration.
- If appropriately applied, Redshift Serverless could unlock new levels of performance and cost-efficiency in data warehousing operations for businesses.
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TechBullion
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Building Trust: How to Overcome Security Challenges in Digital Wallet Usage
- Digital wallets have become the go-to solution for millions who want to streamline their financial lives, but we face an increasingly complex landscape fraught with security challenges that can shake our trust to its very core.
- The popularity of these virtual payment solutions continues to soar; however, they come with a myriad of security challenges that cannot be ignored.
- Factors contributing to security challenges are lack of regulations, inadequate authentication methods, vulnerability to cyber attacks, and data breaches.
- Creating strong passwords, monitoring of transactions, two-factor authentication, and encryption technology protects sensitive data during transactions.
- Collaboration with cybersecurity experts and prioritizing end-to-end encryption helps to enhance safety features. Additionally, biometric verification has gained traction.
- Understanding how digital wallets work, familiarizing oneself with common types of fraud, updating passwords and enabling security features should be part of safe practices.
- Digital wallets have become an essential part of our everyday lives, emphasizing transparency and reliability will be key to overcoming any lingering doubts regarding security challenges.
- With each proactive step towards improved safety measures, trust will grow among consumers and encourage widespread adoption of digital wallets.
- Individuals and companies can overcome such challenges and build trust in digital wallets by following tips and adopting safety measures.
- Digital wallets have revolutionized how we handle money, and they offer unmatched convenience, speed, and security features that can be fortified against potential pitfalls.
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Precisely
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Data Democratization: Transforming Risk Management and Compliance
- Data in organizations is typically managed by two distinct groups: data producers and data consumers.
- Data governance is essential in the age of data democratization, especially for compliance.
- Regulations like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) require clear processes for data access, usage and security, ensuring that customer information is protected at all times.
- One of the primary issues with a project-based approach is the fragmentation it creates, leading to inconsistencies and inefficiencies, which can hinder data accessibility.
- Adopting a modern data management approach that emphasizes quality of data is an important step in overcoming the limitations of traditional data management practices.
- One potential benefit of data democratization is delivering better customer experiences by empowering data consumers to access and analyze customer data.
- Business leaders need to focus on striking a balance between compliance and innovation through effective data management and governance.
- Data governance becomes even more critical as the volume and complexity of data increases.
- Ensuring data quality is critical to any data management strategy - it varies depending on your specific business needs.
- One way to achieve these goals is through the use of centralized data repositories, including data warehouses, data lakes, and MDM solutions.
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Amazon
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Use DeepSeek with Amazon OpenSearch Service vector database and Amazon SageMaker
- DeepSeek-R1 model excels at complex reasoning tasks, when combined with Amazon OpenSearch Service it enables robust Retrieval Augmented Generation (RAG) applications in enterprises.
- This post shows you how to set up RAG using DeepSeek-R1 on Amazon SageMaker with an OpenSearch Service vector database as the knowledge base.
- The OpenSearch Service provides rich capabilities for RAG use cases, as well as vector embedding-powered semantic search.
- You create an OpenSearch connector and model that enable the retrieval_augmented_generation processor within OpenSearch to execute a user query, perform a search, and use DeepSeek to generate a text response.
- You will create a connector to SageMaker with Amazon Titan Text Embeddings V2 to create embeddings for a set of documents with population statistics.
- The post guides you through running a set of scripts to create the entire architecture and data flow including SageMaker endpoint, two IAM roles, OpenSearch connector and model prepared for RAG workflow.
- A RAG workflow essentially involves adding information to the prompt so that the LLM generating the response is more accurate, using search pipelines and OpenSearch retrieval_augmented_generation processor.
- With an OpenSearch based knowledge base of population statistics for two cities (NYC and Miami), Amazon DeepSeek model on SageMaker generates a response to a question on the population changes in New York City and Miami.
- Adapt the code from this post to create your own knowledge base and run your own RAG queries.
- The OpenSearch connector framework is a flexible way to access models hosted on other platforms, while DeepSeek’s reasoning capabilities offer a powerful and cost-effective AI model for building generative applications.
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Siliconangle
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As Trump and Musk scramble everything, investors cool on enterprise tech’s prospects
- President Trump’s chaos and Elon Musk’s mischief with his dubious DOGE coup squad continued unabated, with far too many bizarre, racist and probably illegal actions to list here, not to mention rampant conflicts of interest and security and privacy violations.
- It was a week of disappointing earnings at several big enterprise tech companies, including Alphabet, Amazon and chipmakers AMD, Arm and Qualcomm, as investors squinted to find enough AI upside to justify high capital spending which most definitely is not easing despite the DeepSeek shock and high stock prices.
- In 2025 predictions from theCUBE Research analysts, generative AI remains the big theme, in everything from networking and software development to cybersecurity and consumer services.
- After attending IBM’s first Analyst Day in years, John Furrier contends it’s showing how IBM can help lead in the new AI era where open source could rule.
- Layoffs are on the rise at Salesforce, Workday, Hugging Face, Okta, GM’s Cruise, Sprinkler, Sonos and beyond, in part due to AI.
- AI and data: Bring back reference librarians.
- OpenAI’s ChatGPT can now perform comprehensive research for its users OpenAI seems to be scrambling, as CEO Sam Altman admitted the company was on the “wrong side of history” when it comes to open-source AI.
- AttackIQ acquires DeepSurface to strengthen security posture management.
- New 7AI platform deploys autonomous AI agents to streamline security operations.
- Former SAP, Reltio, and ServiceNow exec Venki Subramanian is Freshworks’ new SVP of product management for CX.
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Sdtimes
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Data is the new petroleum; companies need better pipelines — and better oil-spill clean-up methods
- Data disruptions, similar to oil spills, can halt business operations.
- Enterprises need better storage tanks and secure pipelines to protect valuable data.
- Investing in data resiliency ensures safeguarding and availability of crucial data.
- Backup and recovery must be a priority to prevent growth engine stalling.
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Siliconangle
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Databricks buys the AI-powered data migration startup BladeBridge
- Databricks has acquired data migration startup BladeBridge to help companies migrate their data warehouses to its platform.
- BladeBridge offers tools to automate the migration of workloads from various data warehouses and ETL platforms.
- The startup has developed tools including an Analyzer, a Converter, a Data Recon module, and a Studio to facilitate the data migration process.
- Databricks plans to integrate BladeBridge's tools into its platform to provide customers with a low-cost and risk-free way to migrate to Databricks SQL.
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Amazon
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Handle errors in Apache Flink applications on AWS
- This post discusses the strategies for handling errors in Apache Flink applications, the general principles discussed here apply to stream processing applications at large.
- Before we can talk about how to handle errors in our consumer applications, we first need to consider the two most common types of errors that we encounter: transient and nontransient.
- Retries are mechanisms used to handle transient errors by reprocessing messages that initially failed due to temporary issues.
- DLQs are intended to handle nontransient errors affecting individual messages, not system-wide issues, which require a different approach. Additionally, the use of DLQs might impact the order of messages being processed.
- Using side outputs in Apache Flink, you can direct specific parts of your data stream to different logical streams based on conditions, enabling the efficient management of multiple data flows within a single job.
- After successfully routing problematic messages to a DLQ using side outputs, the next step is determining how to handle these messages downstream.
- Another effective strategy is to store dead letter messages externally from the stream, such as in an Amazon Simple Storage Service (Amazon S3) bucket.
- In this post, we looked at how you can leverage concepts such as retries and dead letter sinks for maintaining the integrity and efficiency of your streaming applications.
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Precisely
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New Year, New Approaches to Tackling IT Operations Management
- IT operations teams need to use modernization and holistic approaches to address the rapid pace of business and manage their environments.
- Assessment of the technology stack is essential to identify any silos, redundancy and other issues affecting IT Operations management.
- ITOps software market is in flux, with AI-focused startups disrupting established players.
- Agile approaches need to be part of the operations practice.
- Automating data capture is important for enhancing AIOps approaches, predictive incident management, and detecting anomalies in IT operations.
- Organizations need to take a hard look at the integrations and connectivity of their on-prem tech stack.
- IT operations require bridging the gap between legacy and modern systems, which requires a strategic, incremental approach.
- One should evaluate their IT ecosystem and take pragmatic steps towards a more resilient, observable, and secure future.
- Modern IT teams cannot rely on a single platform or vendor for operational analytics, security monitoring, and event management, among other things.
- Most IT teams are piecing together the best features from various platforms to create a solution with compatibility, coordination, and scalability necessary to meet their goals.
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Towards Data Science
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Introducing Hoeffding’s Inequality for creating Storage-less Decision Trees
- Hoeffding Trees, a variant of Decision Trees which operate in a streaming fashion can be used for analyzing huge datasets without storing large amounts of data.
- Wassily Hoeffding invented an inequality which quantifies the probability of a random variable's magnitude; randomly creating samples of large data and leading to determine which sampled subset is appropriate for use in a coarser model.
- Hoeffding Trees can be utilized to accurately train a model, even on every tweet made on Twitter while using almost no local memory, by grouping data into subsamples and minimizing costs.
- Hoeffding Trees offer an easy and effective means of reducing memory complexity by keeping track of training data while we also do not have to store the subsamples of data used in the grouping process.
- These Trees are not only used in classification tasks but also regression tasks for other types of data. Such methods can be used for new data points coming from social media.
- Hoeffding Trees offer a feasible solution to the constraint in training decision tree models on large datasets with an endless stream of new data points coming in through social media.
- As opposed to a standard model which finds the entirety of training data, Hoeffding Trees operate while subsampling the correct amount of training data thus building the tree with quite accurate yet incomplete information.
- This article provides a high-level overview of advanced technical methods that could be used in live streaming which required the creation of a workflow which was developed after studying Hoeffding Trees.
- Hoeffding Trees are incredibly fast, cheap and accurate which is made possible by restricting each internal node of the tree to subsamples regardless of the size of the dataset.
- Overall we can safely train our models on a huge volume of data — and stream it — without worrying about RAM and other processing power issues.
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Precisely
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Precisely Women in Technology: Meet Prachi
- Precisely Women in Technology (PWIT) network is a group that brings women in different areas of the organization together to learn from and support one another in various ways.
- Prachi Mujumdar worked as a trainee at Mastek Ltd. and Webify Solutions before joining Precisely as a Technology Architect, a position she has held for the past 18 years.
- Prachi's biggest risk was leaving Mastek Ltd. after working there for 12 years but she's grateful for her growth and the opportunity to work with many talented people at Precisely.
- Prachi hadn't faced any major challenges as a woman in technology until she became a mother, and then she learned the real meaning of work-life balance.
- Prachi advises young women entering the technology industry to believe in themselves and never give up.
- Prachi learned from her lead in her first company that a solution should cover all aspects such as features, benefits, quality, and security.
- To help other women in the field, Prachi advocates for them by being a cheerleader that celebrates their success and encouraging them along the way.
- Precisely makes building and maintaining a diverse workplace a top priority, and there are various programs to support diverse groups.
- Every month, a woman from the PWIT program is invited to share her professional experience as a woman in technology in Precisely's blog.
- Prachi's advice to younger women in the industry is to stay curious, learn new things, and embrace new opportunities.
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Siliconangle
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Aerospike says it has achieved a milestone in NoSQL OLTP performance
- Aerospike Inc. has released a new version of its real-time NoSQL database management system that guarantees strict serializability of ACID transactions at a fraction of the cost of competing systems.
- Strict serializability ensures that transactions appear to execute instantaneously in a total order, which is critical for high-volume online transaction processing scenarios.
- Aerospike achieved consistency for single-record requests with sub-millisecond latency in 2018 and has now expanded data consistency guarantees to distributed multi-object transactions.
- The new release simplifies OLTP development by moving transaction management logic from the application to the database, allowing developers to access the functionality via application program interfaces.
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Fintechnews
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Sumsub Launches Australia DVS Verification for Secure ID Checks
- Sumsub has launched its Australia DVS Verification product to provide real-time, government-backed validation of identity documents such as passports, driving licences, and visas.
- The integration of DVS verification into Sumsub's database validation solution aims to ensure compliance with local anti-money laundering (AML) and Know Your Customer (KYC) regulations while reducing fraud and streamlining onboarding.
- By automating document validation, Sumsub's DVS Verification helps businesses lower operational costs by reducing manual checks, meet identity verification obligations, and enhance fraud prevention through data inconsistency identification.
- As part of its expansion across the Asia-Pacific region, Sumsub is focusing on Australia and plans to support Australian clients with a secure, government-backed process to achieve compliance with AML and KYC standards.
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Siliconangle
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Atombeam raises $20M for its codeword-based data transmission technology
- Atombeam Inc. has raised $20 million in funding for its data transmission technology called Data-as-Codewords.
- Atombeam's technology reduces the storage footprint of files by up to 75% and enhances data security.
- The company plans to commercialize its software with two products, Neurpac and Neurcom.
- Atombeam will utilize the funding to accelerate product development and go-to-market initiatives.
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Dzone
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Data Governance Essentials: Policies and Procedures (Part 6)
- Data governance manages data availability, usability, integrity, and security in an organization through people, processes, policies, standards, and roles.
- Data quality ensures that data is reliable, accurate, and fit for purpose.
- Well-defined policies and procedures play a crucial role in data governance by providing clear guidelines for data management.
- Data quality, policies, and procedures work together to promote accountability, foster trust in data, and enable data-driven decision-making.
- The essential dimensions of data quality are accuracy, completeness, consistency, timeliness, validity, and uniqueness.
- Organizations can implement data quality by executing steps like Data profiling, data cleansing, validation testing, and data governance.
- Data policies are the rules and guidelines that ensure how data is managed and used across the organization and align with legal and regulatory requirements.
- Procedures bring policies to life and provide detailed instructions to ensure policies are effectively implemented and followed.
- Roles and responsibilities of employees are established to define policies and procedures, which may vary depending on the size and policies of the organization.
- Ataccama, Collibra, Oracle EDM, IBM InfoSphere, OvalEdge, Talend Data Fabric, Informatica Axon, Microsoft Purview, and DataRobot are popular tools for implementing data governance, data quality, policies, and procedures.
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