The Business Continuum

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Just as managers ask questions all along the business continuum, BI is responsible for answering those questions along the business continuum. Reports, queries, and analyses can all answer operational, tactical, or strategic questions. An operational report may simply list customer names and addresses and answer the operational question, “Who are our customers?”

Spotlight

ElegantJ BI

The ElegantJ BI Corporate Performance Management (CPM) solution provides simple, affordable, practical features designed to satisfy every user requirement. We specialize in Performance Management and Business Intelligence solutions, and our ElegantJ BI products provide proven analytical and intelligence tools including dashboards, balanced scorecards, graphical mining, cross-tab reporting, and other data mining tools to easily and comprehensively obtain information and manage corporate strategy and tactical activities. Our Corporate Performance Management (CPM) and Business Intelligence (BI) products are robust systems with features and functionality to help your organization develop, monitor, track and produce business performance and enable performance management goals and objectives, ensure appropriate operational management, and analyze the effectiveness of high-level strategy and day-to-day tactical tasks and activities.

OTHER ARTICLES

A Tale of Two Data-Centric Services

Article | April 13, 2020

The acronym DMaaS can refer to two related but separate things: data center management-as-a-service referred to here by its other acronym, DCMaaS and data management-as-a-service. The former looks at infrastructure-level questions such as optimization of data flows in a cloud service, the latter refers to master data management and data preparation as applied to federated cloud services.DCMaaS has been under development for some years; DMaaS is slightly younger and is a product of the growing interest in machine learning and big data analytics, along with increasing concern over privacy, security, and compliance in a cloud environment.DMaaS responds to a developing concern over data quality in machine learning due to the large amount of data that must be used for training and the inherent dangers posed by divergence in data structure from multiple sources. To use the rapidly growing array of cloud data, including public cloud information and corporate internal information from hybrid clouds, you must aggregate data in a normalized way so it can be available for model training and processing with ML algorithms. As data volumes and data diversity increase, this becomes increasingly difficult.

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How big data can help the homeless

Article | April 13, 2020

Homeless policy needs to join the big data revolution. A data tsunami is transforming our world. Ninety percent of existing data was created in the last two years, and Silicon Valley is leveraging it with powerful analytics to create self-driving cars and to revolutionize business decision-making in ways that drive innovation and efficiency.Unfortunately, this revolution has yet to help the homeless. It is not due to a lack of data. Sacramento alone maintains data on half a million service interactions with more than 65,000 homeless individuals. California is considering integrating the data from its 44 continuums of care to create a richer pool of data. Additionally, researchers are uncovering troves of relevant information in educational and social service databases.These data, however, are only useful if they are aggressively mined for insights, looking for problems to solve and successful practices to replicate. At that juncture California falls short.

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How can we democratize machine learning on IoT devices

Article | April 13, 2020

TinyML, as a concept, concerns the running of ML inference on Ultra Low-Power (ULP 1mW) microcontrollers found on IoT devices. Yet today, various challenges still limit the effective execution of TinyML in the embedded IoT world. As both a concept and community, it is still under development.Here at Ericsson, the focus of our TinyML as-a-Service (TinyMLaaS) activity is to democratize TinyML, enabling manufacturers to start their AI businesses using TinyML, which runs on 8, 16 and 32 bit microcontrollers.Our goal is to make the execution of ML tasks possible and easy in a specific class of devices. These devices are characterized by very constrained hardware and software resources such as sensor and actuator nodes based on these microcontrollers.Below, we present how we can bind the as-a-service model to TinyML. We will provide a high-level technical overview of our concept and introduce the design requirements and building blocks which characterize this emerging paradigm.

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Predictive Analytics: Enabling Businesses Achieve Accurate Data Prediction using AI

Article | April 13, 2020

We are living in the age of Big Data, and data has become the heart and the most valuable asset for businesses across industry verticals. In the hyper-competitive market that exists today, data acts as a major contributor to achieving business intelligence and brand equity. Thus, effective data management is the key to accelerating the success of businesses. For effective data management to take place, organizations must ensure that the data that is used is accurate and reliable. With the advent of AI, businesses can now leverage machine learning to predict outcomes using historical data. This is called predictive analytics. With predictive analytics, organizations can predict anything from customer turnover to forecasting equipment maintenance. Moreover, the data that is acquired through predictive analytics is of high quality and very accurate. Let us take a look at how AI enables accurate data prediction and helps businesses to equip themselves for the digital future.

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Spotlight

ElegantJ BI

The ElegantJ BI Corporate Performance Management (CPM) solution provides simple, affordable, practical features designed to satisfy every user requirement. We specialize in Performance Management and Business Intelligence solutions, and our ElegantJ BI products provide proven analytical and intelligence tools including dashboards, balanced scorecards, graphical mining, cross-tab reporting, and other data mining tools to easily and comprehensively obtain information and manage corporate strategy and tactical activities. Our Corporate Performance Management (CPM) and Business Intelligence (BI) products are robust systems with features and functionality to help your organization develop, monitor, track and produce business performance and enable performance management goals and objectives, ensure appropriate operational management, and analyze the effectiveness of high-level strategy and day-to-day tactical tasks and activities.

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