R Shiny for Cross Industry, Cross Function Data Visualization

| November 21, 2018

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The increasing access to Big Data in this world of connectivity has opened up the possibility of gaining deep insights that can help businesses take relevant, strategic decisions that can spur growth. No wonder then that the Big Data market is expected to grow from USD 28.65 Billion in 2016 to USD 66.79 Billion by 2021, at a high Compound Annual Growth Rate (CAGR) of 18.45%, according to MarketsandMarkets Research. The growth in Big Data in itself is not as significant as the ability to cull insights and forecast future trends. As a result, Zion Market Research expects the global predictive analytics market to grow at a CAGR of 21 per cent from USD 3.49 billion in 2016 to approximately USD 10.95 billion by 2022. Given the complexity of data, data visualization tools have become critical to presenting the data in ways that can help understand the dynamics between data elements better. Charts, videos, infographics and even virtual reality and augmented reality presentations are being used for more engaging and intuitive insights.

Spotlight

Mobileum

Mobileum helps telecom service providers leverage the power of predictive analytics and real-time insights to drive game-changing business transformation. Mobileum helps CSPs leverage the power of predictive analytics to deliver monetizable insights that drive business transformation at 617CSPs across 150 countries. Mobileum’s Wisdom-Action platform powers solutions across domains such as Voice and Data roaming, IoT/M2M, Video, WiFi Hetnets, Travel, Counter fraud, Data abuse, and CEM. Mobileum enables CSPs to gain deep understanding of network and subscriber behavior, and use those insights to improve service adoption, arrest churn, deliver superior customer experience, and benefit from emerging business models while preventing fraud and revenue leakage. The company is headquartered in Santa Clara, CA (USA), with key regional offices in Brussels, Bangalore, Dublin, Dubai, Hong Kong, Mumbai, Gurgaon, Singapore, Uruguay, and Argentina. Mobileum is a privately held company founded in 200

OTHER ARTICLES

Data Analytics the Force Behind the IoT Evolution

Article | April 3, 2020

Primarily,the IoT stack is going beyond merely ingesting data to data analytics and management, with a focus on real-time analysis and autonomous AI capacities. Enterprises are finding more advanced ways to apply IoT for better and more profitable outcomes. IoT platforms have evolved to use standard open-source protocols and components. Now enterprises are primarily focusing on resolving business problems such as predictive maintenance or usage of smart devices to streamline business operations.Platforms focus on similar things, but early attempts at the creation of highly discrete solutions around specific use cases in place of broad platforms, have been successful. That means more vendors offer more choices for customers, to broaden the chances for success. Clearly, IoT platforms actually sit at the heart of value creation in the IoT.

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Advanced Data and Analytics Can Add Value in Private Equity Industry!

Article | January 6, 2021

As the organizations go digital the amount of data generated whether in-house or from outside is humongous. In fact, this data keeps increasing with every tick of the clock. There is no doubt about the fact that most of this data can be junk, however, at the same time this is also the data set from where an organization can get a whole lot of insight about itself. It is a given that organizations that don’t use this generated data to build value to their organization are prone to speed up their obsolescence or might be at the edge of losing the competitive edge in the market. Interestingly it is not just the larger firms that can harness this data and analytics to improve their overall performance while achieving operational excellence. Even the small size private equity firms can also leverage this data to create value and develop competitive edge. Thus private equity firms can achieve a high return on an initial investment that is low. Private Equity industry is skeptical about using data and analytics citing the reason that it is meant for larger firms or the firms that have deep pockets, which can afford the revamping cost or can replace their technology infrastructure. While there are few private equity investment professionals who may want to use this advanced data and analytics but are not able to do so for the lack of required knowledge. US Private Equity Firms are trying to understand the importance of advanced data and analytics and are thus seeking professionals with the expertise in dealing with data and advanced analytics. For private equity firms it is imperative to comprehend that data and analytics’ ability is to select the various use cases, which will offer the huge promise for creating value. Top Private Equity firms all over the world can utilize those use cases and create quick wins, which will in turn build momentum for wider transformation of businesses. Pinpointing the right use cases needs strategic thinking by private equity investment professionals, as they work on filling the relevant gaps or even address vulnerabilities. Private Equity professionals most of the time are also found thinking operationally to recognize where can they find the available data. Top private equity firms in the US have to realize that the insights which Big data and advanced analytics offer can result in an incredible opportunity for the growth of private equity industry. As Private Equity firms realize the potential and the power of big data and analytics they will understand the invaluableness of the insights offered by big data and analytics. Private Equity firms can use the analytics insights to study any target organization including its competitive position in the market and plan their next move that may include aggressive bidding for organizations that have shown promise for growth or leaving the organization that is stuffed with loads of underlying issues. But for all these and also to build careers in private equity it is important to have reputed qualification as well. A qualified private equity investment professional will be able to devise information-backed strategies in no time at all. In addition, with Big Data and analytics in place, private equity firms can let go of numerous tasks that are done manually and let the technology do the dirty work. There have been various studies that show how big data and analytics can help a private Equity firm.

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How big data can help the homeless

Article | March 12, 2020

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Evolution of capabilities of Data Platforms & data ecosystem

Article | October 27, 2020

Data Platforms and frameworks have been constantly evolving. At some point of time; we are excited by Hadoop (well for almost 10 years); followed by Snowflake or as I say Snowflake Blizzard (who managed to launch biggest IPO win historically) and the Google (Google solves problems and serves use cases in a way that few companies can match). The end of the data warehouse Once upon a time, life was simple; or at least, the basic approach to Business Intelligence was fairly easy to describe… A process of collecting information from systems, building a repository of consistent data, and bolting on one or more reporting and visualisation tools which presented information to users. Data used to be managed in expensive, slow, inaccessible SQL data warehouses. SQL systems were notorious for their lack of scalability. Their demise is coming from a few technological advances. One of these is the ubiquitous, and growing, Hadoop. On April 1, 2006, Apache Hadoop was unleashed upon Silicon Valley. 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Examples of these include the Kubernetes container management framework, TensorFlow machine learning platform and the Apache Beam data processing programming model. GCP also uses open-source offerings in its cloud while treating third-party data and analytics providers as first-class citizens on its cloud and providing unified billing for its customers. The examples of the latter include DataStax, Redis Labs, InfluxData, MongoDB, Elastic, Neo4j and Confluent. Silicon Valley tried to make Hadoop work. The technology was extremely complicated and nearly impossible to use efficiently. Hadoop’s lack of speed was compounded by its focus on unstructured data — you had to be a “flip-flop wearing” data scientist to truly make use of it. Unstructured datasets are very difficult to query and analyze without deep knowledge of computer science. At one point, Gartner estimated that 70% of Hadoop deployments would not achieve the goal of cost savings and revenue growth, mainly due to insufficient skills and technical integration difficulties. And seventy percent seems like an understatement. Data storage through the years: from GFS to Snowflake or Snowflake blizzard Developing in parallel with Hadoop’s journey was that of Marcin Zukowski — co-founder and CEO of Vectorwise. Marcin took the data warehouse in another direction, to the world of advanced vector processing. Despite being almost unheard of among the general public, Snowflake was actually founded back in 2012. Firstly, Snowflake is not a consumer tech firm like Netflix or Uber. It's business-to-business only, which may explain its high valuation – enterprise companies are often seen as a more "stable" investment. In short, Snowflake helps businesses manage data that's stored on the cloud. 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For those of us not in the details of the Snowflake schema, it is a logical arrangement of tables in a multidimensional database such that the entity-relationship diagram resembles a snowflake shape. … When it is completely normalized along all the dimension tables, the resultant structure resembles a snowflake with the fact table in the middle. Needless to say, the “snowflake” schema is as far from Hadoop’s design philosophy as technically possible. While Silicon Valley was headed toward a dead end, Snowflake captured an entire cloud data market.

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Spotlight

Mobileum

Mobileum helps telecom service providers leverage the power of predictive analytics and real-time insights to drive game-changing business transformation. Mobileum helps CSPs leverage the power of predictive analytics to deliver monetizable insights that drive business transformation at 617CSPs across 150 countries. Mobileum’s Wisdom-Action platform powers solutions across domains such as Voice and Data roaming, IoT/M2M, Video, WiFi Hetnets, Travel, Counter fraud, Data abuse, and CEM. Mobileum enables CSPs to gain deep understanding of network and subscriber behavior, and use those insights to improve service adoption, arrest churn, deliver superior customer experience, and benefit from emerging business models while preventing fraud and revenue leakage. The company is headquartered in Santa Clara, CA (USA), with key regional offices in Brussels, Bangalore, Dublin, Dubai, Hong Kong, Mumbai, Gurgaon, Singapore, Uruguay, and Argentina. Mobileum is a privately held company founded in 200

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