Golang for Data Analytics Applications is a suitable choice because of its standard official libraries which enable easy data parsing, sorting, analyzing and visualizing.
IACT Global provides Big Data Certification in support with IBM Big Insight.To know more about the course connect with the counselors of IACT Global
http://www.iactglobal.in/course.aspx?coursename=big-data-vc
Gianluigi Vigano, Senior Architect and Fouad Teban, Regional Presales Manager...Dataconomy Media
Gianluigi Vigano, Senior Architect and Fouad Teban, Regional Presales Manager at HPE, presented "Using advanced analytics functions of HPE Vertica for the following use cases: IoT, clickstream, machine data, integration with Hadoop & Kafka …" as part of the Big Data, Budapest v 3.0 meetup organised on the 19th of May 2016 at Skyscanner's headquarters.
Digicorp is developing Electronic Health Records (EHR) solutions for various US-based clinics and Nursing Homes (LTC) since 2004.
The latest EHR for a client is the most advanced of them all. It is used by more than 250 doctors and handles millions of transactions every month. It is CCHIT, Surescripts certified and has received 5 star usability rating.
Digicorp's own DeltaCare helps nursing homes improve quality of care, lower expenses and reduce cost of care by implementing EHR technology. DeltaCare is the proven and trusted name for long term care EHR solutions.
Data Con LA 2019 - Big Data Modeling with Spark SQL: Make data valuable by Ja...Data Con LA
In this Data age, business applications generate big data. To generate value out of large scale data applications, data models are the key. Data models serve various purposes, and it is essential to show reliable insights in a timely fashion. This session will cover the technical aspect of leveraging Spark's distributed engine to process Big data to generate insights. It includes a few aspects to optimize processes with Spark SQL. Come join me to explore the process of making data interesting!
IACT Global provides Big Data Certification in support with IBM Big Insight.To know more about the course connect with the counselors of IACT Global
http://www.iactglobal.in/course.aspx?coursename=big-data-vc
Gianluigi Vigano, Senior Architect and Fouad Teban, Regional Presales Manager...Dataconomy Media
Gianluigi Vigano, Senior Architect and Fouad Teban, Regional Presales Manager at HPE, presented "Using advanced analytics functions of HPE Vertica for the following use cases: IoT, clickstream, machine data, integration with Hadoop & Kafka …" as part of the Big Data, Budapest v 3.0 meetup organised on the 19th of May 2016 at Skyscanner's headquarters.
Digicorp is developing Electronic Health Records (EHR) solutions for various US-based clinics and Nursing Homes (LTC) since 2004.
The latest EHR for a client is the most advanced of them all. It is used by more than 250 doctors and handles millions of transactions every month. It is CCHIT, Surescripts certified and has received 5 star usability rating.
Digicorp's own DeltaCare helps nursing homes improve quality of care, lower expenses and reduce cost of care by implementing EHR technology. DeltaCare is the proven and trusted name for long term care EHR solutions.
Data Con LA 2019 - Big Data Modeling with Spark SQL: Make data valuable by Ja...Data Con LA
In this Data age, business applications generate big data. To generate value out of large scale data applications, data models are the key. Data models serve various purposes, and it is essential to show reliable insights in a timely fashion. This session will cover the technical aspect of leveraging Spark's distributed engine to process Big data to generate insights. It includes a few aspects to optimize processes with Spark SQL. Come join me to explore the process of making data interesting!
Business intelligence tools to handle big dataIshucs
Business intelligence (BI) is a technology-driven process for analyzing data and delivering actionable information that helps executives, managers and workers make informed business decisions.
Scanner Data
In these slides the author presents the issues and challenges related to dealing with datasets of big size such as those involved in the Scanner Data project at Istat. He illustrates IT architecture backing the testing phase of the project, currently in place, and the ideas for the production architecture. The motivations behind the design are explained as well as the solutions introduced as part of a larger scope approach to the modernization of tools and techniques used for data storage and processing in Istat, envisioning the future challenges posed by the adoption of Big Data and Data Science in NSIs.
http://www.istat.it/en/archive/168897
http://www.istat.it/it/archivio/168890
UNIFi and HavasMedia Case Study - Creating New Customer Value with DataUNIFI Software
This case study presentation discusses how Havas Media uses UNIFi Software on Hadoop for data enrichment, blending and integration to:
- Use substantially more data sets to add context to existing campaign results
- Allow many more users within the company to access and analyze the data sets of their choice without relying on programmers
Analytical Systems Evolution: From Excel to Big Data Platforms and Data LakesProvectus
Maxim Tereschenko (BigData Lead, Provectus) with the talk "Analytical Systems Evolution - From Excel to Big Data Platforms and Data Lakes".
Description: For the last ten years, analytical systems have changed dramatically. From Excel and Data Warehouses, we came to Big Data platforms and Data Lakes. It is no longer fantasy to communicate with the analytical system by voice or to wander in 3D glasses among the visualizations of the data. In scope of the speech, I want to follow this evolution, identify its main trends and fantasize about the future.
The Alteryx Designer solves this by delivering an intuitive workflow for data blending and advanced analytics that leads to deeper insights in hours, not the weeks typical of traditional approaches! The Alteryx Designer empowers data analysts by combining data blending, predictive analytics, spatial analytics, and reporting, visualization and analytic apps into one workflow.
What is Big Data? This slide shows an explanation, knowledge and extraction techniques of big data in a factory setting, to maintain and measure performance and improve productivity in your factory, therefore increasing efficiency and profit.
Product-thinking is making a big impact in the data world with the rise of Data Products, Data Product Managers, data mesh, and treating “Data as a Product.” But Honest, No-BS: What is a Data Product? And what key questions should we ask ourselves while developing them? Tim Gasper (VP of Product, data.world), will walk through the Data Product ABCs as a way to make treating data as a product way simpler: Accountability, Boundaries, Contracts and Expectations, Downstream Consumers, and Explicit Knowledge.
Top Big data Analytics tools: Emerging trends and Best practicesSpringPeople
For many IT experts, big data analytics tools and technologies are now a top priority. Let's find out the top big data analytics tools in this slide to initialize and advance the process of big data analysis.
Business intelligence tools to handle big dataIshucs
Business intelligence (BI) is a technology-driven process for analyzing data and delivering actionable information that helps executives, managers and workers make informed business decisions.
Scanner Data
In these slides the author presents the issues and challenges related to dealing with datasets of big size such as those involved in the Scanner Data project at Istat. He illustrates IT architecture backing the testing phase of the project, currently in place, and the ideas for the production architecture. The motivations behind the design are explained as well as the solutions introduced as part of a larger scope approach to the modernization of tools and techniques used for data storage and processing in Istat, envisioning the future challenges posed by the adoption of Big Data and Data Science in NSIs.
http://www.istat.it/en/archive/168897
http://www.istat.it/it/archivio/168890
UNIFi and HavasMedia Case Study - Creating New Customer Value with DataUNIFI Software
This case study presentation discusses how Havas Media uses UNIFi Software on Hadoop for data enrichment, blending and integration to:
- Use substantially more data sets to add context to existing campaign results
- Allow many more users within the company to access and analyze the data sets of their choice without relying on programmers
Analytical Systems Evolution: From Excel to Big Data Platforms and Data LakesProvectus
Maxim Tereschenko (BigData Lead, Provectus) with the talk "Analytical Systems Evolution - From Excel to Big Data Platforms and Data Lakes".
Description: For the last ten years, analytical systems have changed dramatically. From Excel and Data Warehouses, we came to Big Data platforms and Data Lakes. It is no longer fantasy to communicate with the analytical system by voice or to wander in 3D glasses among the visualizations of the data. In scope of the speech, I want to follow this evolution, identify its main trends and fantasize about the future.
The Alteryx Designer solves this by delivering an intuitive workflow for data blending and advanced analytics that leads to deeper insights in hours, not the weeks typical of traditional approaches! The Alteryx Designer empowers data analysts by combining data blending, predictive analytics, spatial analytics, and reporting, visualization and analytic apps into one workflow.
What is Big Data? This slide shows an explanation, knowledge and extraction techniques of big data in a factory setting, to maintain and measure performance and improve productivity in your factory, therefore increasing efficiency and profit.
Product-thinking is making a big impact in the data world with the rise of Data Products, Data Product Managers, data mesh, and treating “Data as a Product.” But Honest, No-BS: What is a Data Product? And what key questions should we ask ourselves while developing them? Tim Gasper (VP of Product, data.world), will walk through the Data Product ABCs as a way to make treating data as a product way simpler: Accountability, Boundaries, Contracts and Expectations, Downstream Consumers, and Explicit Knowledge.
Top Big data Analytics tools: Emerging trends and Best practicesSpringPeople
For many IT experts, big data analytics tools and technologies are now a top priority. Let's find out the top big data analytics tools in this slide to initialize and advance the process of big data analysis.
Data analytics is important because it helps businesses
optimize their performances. Implementing it into the
business model means companies can help reduce
costs by identifying more efficient ways of doing
business and by storing large amounts of data. A
company can also use data analytics to make better
business decisions and help analyze customer trends
and satisfaction, which can lead to new—and better—
products and services
Revolution in Business Analytics-Zika Virus ExampleBardess Group
Even from the “man in the street” perspective, there is a sense that we are living in an increasingly algorithmic world. Self-driving cars, pizza delivery by drone, and smart houses are commonplace. The technologies enabling this revolution are both simultaneously mature and evolving rapidly.
In this session, we’ll took a look at a real world problem, the recent global outbreak of the ZIka virus, and used data analytics technologies to gain valuable insights that can assist authorities and the general public to understand and potentially prevent the spread of this disease.
Bardess Group, a sponsor of the event and business analytics consulting firm, will demonstrate how huge, extremely jagged data from a variety of sources can be collected and prepared and rapidly made available for analysis. Advanced machine learning and predictive analysis further enhance the value of those insights.
Finally, Bardess will make the case that using a systematic approach to conceptually visualize the strategic journey to insightful business analytics, the analytics value chain, can assist any organization prepare for this revolution in analytics.
Also see http://cloudera.qlik.com for the demos.
March Towards Big Data - Big Data Implementation, Migration, Ingestion, Manag...Experfy
Gartner, IBM, Accenture and many others have asserted that 80% or more of the world’s information is unstructured – and inherently hard to analyze. What does that mean? And what is required to extract insight from unstructured data?
Unstructured data is infinitely variable in quality and format, because it is produced by humans who can be fastidious, unpredictable, ill-informed, or even cynical, but always unique, not standard in any way. Recent advances in natural language processing provides the notion that unstructured content can be included in data analysis.
Serious growth and value companies are committed to data. The exponential growth of Big Data has posed major challenges in data governance and data analysis. Good data governance is pivotal for business growth.
Therefore, it is of paramount importance to slice and dice Big Data that addresses data governance and data analysis issues. In order to support high quality business decision making, it is important to fully harness the potential of Big Data by implementing proper Data Migration, Data Ingestion, Data Management, Data Analysis, Data Visualization and Data Virtualization tools.
Check it out: https://www.experfy.com/training/courses/march-towards-big-data-big-data-implementation-migration-ingestion-management-visualization
How a Logical Data Fabric Enhances the Customer 360 ViewDenodo
Watch full webinar here: https://bit.ly/3GI802M
Organisations have struggled for years in understanding their customers, this has mainly been due to not having the right data available at the right point in time. In this session we will discuss the role of Data Virtualization in providing customer 360 degree view and look at some of the success stories our customers have told us about.
Using Data Mining Technique, Loginworks is offering the web data mining solutions. One of the leading Data mining companies delivering data mining services.
https://www.loginworks.com/data-mining/
Why Your Data Science Architecture Should Include a Data Virtualization Tool ...Denodo
Watch full webinar here: https://bit.ly/35FUn32
Presented at CDAO New Zealand
Advanced data science techniques, like machine learning, have proven an extremely useful tool to derive valuable insights from existing data. Platforms like Spark, and complex libraries for R, Python, and Scala put advanced techniques at the fingertips of the data scientists.
However, most architecture laid out to enable data scientists miss two key challenges:
- Data scientists spend most of their time looking for the right data and massaging it into a usable format
- Results and algorithms created by data scientists often stay out of the reach of regular data analysts and business users
Watch this session on-demand to understand how data virtualization offers an alternative to address these issues and can accelerate data acquisition and massaging. And a customer story on the use of Machine Learning with data virtualization.
They serve customers across small, Mid-size and Enterprise segments-ranging from $50M to $50B in size-in multiple industries.
Services include: End-to-end implementations, managed services, project management, training, integrations with enterprise systems, and business process re-engineering.
Course 8 : How to start your big data project by Eric Rodriguez Betacowork
For more info about our Big Data courses, check out our website ➡️ https://www.betacowork.com/big-data/
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"Data is the new oil" - Many companies and professionals do not know how to use their data or are not aware of the added value they could gain from it.
It is in response to these problems that the project “Brussels: The Beating Heart of Big Data” was born.
This project, financed by the Region of Brussels Capital and organised by Betacowork, offers 3 training cycles of 10 courses on big data, at both beginner and advanced levels. These 3 cycles will be followed by a Hackathon weekend.
No prerequisites are required to start these courses. The aim of these courses is to familiarize participants with the principles of Big Data.
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For more info about our Big Data courses, check out our website ➡️ https://www.betacowork.com/big-data/
Lecture 1.13 & 1.14 &1.15_Business Profiles in Big Data.pptxRATISHKUMAR32
The presentation contain the business profiles in big data analytics. through this ppt user can learn about the different case studies such as facebook and walmart. This ppt contain the information and seven characteristics that are required to learn the basics of big data.
As a Golang development Company, Gowitek specialize in Golang development. We leverage Golangs features such as concurrency, scalability, cross-platform support, garbage collection and more.
Golang for Data Analytics Applications is a suitable choice because of its standard official libraries which enable easy data parsing, sorting, analyzing and visualizing.
Pump Monitoring Systems powered by remote IoT Monitoring solutions help track pump performance parameters in terms of temperature, vibrations, voltage fluctuations and more. It helps to make predictive decisions for improved maintenance.
Centrifugal Pumps are one of the most commonly used pumps for transferring liquids and so Centrifugal Pumps maintenance is quite essential in order to keep it free from Centrifugal Pumps Problems.
IIoT Sensors for Centrifugal Pump help to pick data on operational parameters such as heat, presence of gas, vapor and more to ensure damage can be prevented.
Golang is a lightweight, new open-source language which has several features that make automated and manual testing easier. Due to feature-rich standard library support, it provides a desirable environment for running and writing tests.
Spare Part Manufacturing Company is looking for a Big Data analytics solution that will pull data from the Datalog of the server to determine various issues
An Energy Management System is any digital aided method of conseving energy. One such method is to use IoT Data Analytics applications to track energy consumption. It can perform various functions such as predict downtime of electronic equipment, determine energy-wasting equipment and more. Read here for a more detailed understanding about how this works.
Golang is a lightweight, new open-source language which has several features that make automated and manual testing easier. Due to feature-rich standard library support, it provides a desirable environment for running and writing tests. Go describes a way to write automated tests that are automatically excluded from the compiled executable. Thus this test suite runs at the development time. It also displays which lines were exercised by tests, and which were not and provides complete code coverage analysis.
Pump Monitoring Systems powered by remote IoT Monitoring solutions help track pump performance parameters in terms of temperature, vibrations, voltage fluctuations and more. It helps to take predictive decisions for improved maintenance. http://bit.ly/2YFOoFV
IoT security compliance checklist is essential to ensure IoT security. Here is a complete it security audit checklist for ensuring the security of IoT Devices in real time.
IoT Monitoring System For Intelligent Pumps Mining can lead to business benefits such as cost savings in business processes, improve production efficiency, better asset utilization, Predictive maintenance, and improved safety.http://bit.ly/2UpePB7
As a Golang development Company, Gowitek specialize in Golang development. We leverage Golang features such as concurrency, scalability, cross-platform support, garbage collection and more.
Golang is suitable for IoT applications due to its inherent concurrency and scalability features. Coupled with its secure code and cross-platform support it helps develop comprehensive IoT applications that are safe and support connectivity of numerous devices.
Now -a day's artificial intelligence Applications are bringing massive changes in technology solutions. Artificial intelligence applications are making progress towards customer interaction, accessibility, purchase experience, user experience financial planning and many more. Features like self-correction, Machine learning, and Logical Reasoning are able to mimic human intelligence. Artificial intelligence applications also help businesses in various ways such as improve the use of their resources, with a visible effect on their bottom line.
Pump Monitoring Systems powered by remote IoT Monitoring solutions help track pump performance parameters in terms of temperature, vibrations, voltage fluctuations and more. It helps to take predictive decisions for improved maintenance.
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
2. Introduction
• Organizations collect vast
amounts of data.
• This mass of data tell facts that
are relevant for key decision
making.
• Data insights help businesses
understand challenges and devise
solutions.
• Due to this, demand for Data
Analytics applications is on the
rise.
3. Golang
• Golang is a modern
language which is
procedural, imperative
and modular.
• Google’s Golang helps
build scalable and
efficient solutions.
• Go is suitable fit for Data
Analytics solutions and
at every step of the data
analytics process.
4. Data Gathering
• Data Analytics application should be able to collect and
store vast amounts of error free data that takes into
account logical, cost and privacy considerations.
• It should also be able to store incoming data that can be
modeled and reported while also joining data from
multiple sources in a logical manner.
• There are many Databases in Golang such as InfluxDB,
Minio, CokroachDB. Go has several APIs for all of the
commonly used datastores such as Mongo and Postgres.
This kind of resource backup makes it easy for Golang Data
Analytics applications to collect and organize data.
5. Processing and Analyzing Data
Sets
• The next step is to Process data sets to clean up messy raw
data.
• Algorithms are applied to build and validate data models
while performing machine learning/ deep learning.
• In Go the gonum organization powers data science
computations by providing numerical functionality. Floats,
Matrix, Stats, gograph are Golang projects related to data
analytics, statistics and arithmetic.
• They help develop arithmetically sound and comprehensive
Data Analytics applications.
6. Visualizing and
Communicating Results
• Good data visualization of results means sound decision
making by users.
• Application should convey results of investigation in a way
that makes sense and can be easily communicated.
• Golang projects such as gophernotes, dashing-go and
gonum plotting make it easy to create powerful
visualizations. Creating Custom APIs for this purpose and
utilizing resources such as D3 contribute to the
comprehensiveness of Golang Data Analytics applications.
7. Conclusion
• At Gowitek we have worked on several Data
Analytics projects spanning industries such as
Agriculture, Manufacturing, Healthcare, Retail and
more.
• Scalable and efficient Data Analytics
solutions strongly support business goals and solve
core challenges.