The document provides an overview of the mobile gaming sector including key metrics and subsectors. It summarizes that there are over 4,000 companies in the mobile gaming feed covering game developers, platforms, publishers and enablers that have raised $8.5 billion total. The top markets for investment are casual multi-genre game developers and AR-enabled mid-core game developers. Notable companies mentioned include Zynga, Netmarble Games Corporation, and Rovio.
Tracxn - Top Business Models - Mobile - Dec 2021Tracxn
Today's top #BusinessModel report is on Mobile rebrand.ly/yjlikmn
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M&A Hitting New Highs, GamesBeat presentationAlina Soltys
Presentation given by Alina Soltys at GamesBeat - September 2014
Provides overview of strong Gaming M&A market along with discussion on trends affecting new areas of growth.
Tracxn - Top Business Models - Mobile Tech - Jan 2022Tracxn
Tracxn's proprietary #taxonomy brings to you top #BusinessModels in Mobile rebrand.ly/rq1h5s6
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Tracxn's proprietary #taxonomy brings to you top #BusinessModels in Top Business Models in Sustainability Tech Report https://tracxn.com/fm/dl/Gymr7Akd3ybI
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Tracxn - Southeast Asia Tech Monthly Funding ReportTracxn
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Tracxn - Top Business Models in Sustainability Tech - 26 Oct 2023Tracxn
Tracxn's proprietary #taxonomy brings to you top #BusinessModels in Top Business Models in Sustainability Tech Report https://tracxn.com/fm/dl/MnFvJ6UKhc9y
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Tracxn - United States Tech Monthly Funding ReportTracxn
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Tracxn - Top Business Models in High Tech - 27 Oct 2023Tracxn
Today's top #BusinessModel report is on Top Business Models in High Tech Report https://tracxn.com/platform/file-manager/file/ZmlsZUlkPUx5U0Qya01PRm9QbHJCTUM0UG9QVFJUeWJselF0RHJzSGU0dFlWMG5uWEk%3D
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Tracxn - Top Business Models in Vietnam Tech - 20 Oct 2023Tracxn
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Tracxn - Top Business Models in Singapore Tech - 19 Oct 2023Tracxn
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Tracxn - Top Business Models in New Zealand Tech - 19 Oct 2023Tracxn
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Tracxn - Top Business Models in United Kingdom Tech - 18 Oct 2023Tracxn
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Tracxn -Top Business Models in Transportation and Logistics Tech - 17 Oct 2023Tracxn
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Tracxn - United Kingdom Tech Monthly Funding ReportTracxn
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Tracxn - Top Business Models in Sustainability Tech - 26 Oct 2023Tracxn
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Tracxn - United States Tech Monthly Funding ReportTracxn
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Enhanced Enterprise Intelligence with your personal AI Data Copilot.pdfGetInData
Recently we have observed the rise of open-source Large Language Models (LLMs) that are community-driven or developed by the AI market leaders, such as Meta (Llama3), Databricks (DBRX) and Snowflake (Arctic). On the other hand, there is a growth in interest in specialized, carefully fine-tuned yet relatively small models that can efficiently assist programmers in day-to-day tasks. Finally, Retrieval-Augmented Generation (RAG) architectures have gained a lot of traction as the preferred approach for LLMs context and prompt augmentation for building conversational SQL data copilots, code copilots and chatbots.
In this presentation, we will show how we built upon these three concepts a robust Data Copilot that can help to democratize access to company data assets and boost performance of everyone working with data platforms.
Why do we need yet another (open-source ) Copilot?
How can we build one?
Architecture and evaluation
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Learn SQL from basic queries to Advance queriesmanishkhaire30
Dive into the world of data analysis with our comprehensive guide on mastering SQL! This presentation offers a practical approach to learning SQL, focusing on real-world applications and hands-on practice. Whether you're a beginner or looking to sharpen your skills, this guide provides the tools you need to extract, analyze, and interpret data effectively.
Key Highlights:
Foundations of SQL: Understand the basics of SQL, including data retrieval, filtering, and aggregation.
Advanced Queries: Learn to craft complex queries to uncover deep insights from your data.
Data Trends and Patterns: Discover how to identify and interpret trends and patterns in your datasets.
Practical Examples: Follow step-by-step examples to apply SQL techniques in real-world scenarios.
Actionable Insights: Gain the skills to derive actionable insights that drive informed decision-making.
Join us on this journey to enhance your data analysis capabilities and unlock the full potential of SQL. Perfect for data enthusiasts, analysts, and anyone eager to harness the power of data!
#DataAnalysis #SQL #LearningSQL #DataInsights #DataScience #Analytics
The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data LakeWalaa Eldin Moustafa
Dynamic policy enforcement is becoming an increasingly important topic in today’s world where data privacy and compliance is a top priority for companies, individuals, and regulators alike. In these slides, we discuss how LinkedIn implements a powerful dynamic policy enforcement engine, called ViewShift, and integrates it within its data lake. We show the query engine architecture and how catalog implementations can automatically route table resolutions to compliance-enforcing SQL views. Such views have a set of very interesting properties: (1) They are auto-generated from declarative data annotations. (2) They respect user-level consent and preferences (3) They are context-aware, encoding a different set of transformations for different use cases (4) They are portable; while the SQL logic is only implemented in one SQL dialect, it is accessible in all engines.
#SQL #Views #Privacy #Compliance #DataLake
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Unleashing the Power of Data_ Choosing a Trusted Analytics Platform.pdfEnterprise Wired
In this guide, we'll explore the key considerations and features to look for when choosing a Trusted analytics platform that meets your organization's needs and delivers actionable intelligence you can trust.
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...sameer shah
"Join us for STATATHON, a dynamic 2-day event dedicated to exploring statistical knowledge and its real-world applications. From theory to practice, participants engage in intensive learning sessions, workshops, and challenges, fostering a deeper understanding of statistical methodologies and their significance in various fields."
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97. Some more Sector Reports you might want to check out
Join 4000+ people taking sharper decisions with Tracxn
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