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Presentation by Erik van der Hoeven (Wisdom as a Service) at the Data Vault M...Patrick Van Renterghem
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Presentation by Erik van der Hoeven (Wisdom as a Service) at the Data Vault M...Patrick Van Renterghem
Erik van der Hoeven explains how to transform data into wisdom. At a major Dutch bank, he informs our conference participants about the future architecture, the WhereScape pilot, the first DV 2.0 and the first EDM implementation. Conclusion: integrating WhereScape and Denodo is not out of the box
The number of databases and database technologies has grown considerably. Databases are also becoming more and more application specific. Neither end of the spectrum is easy to manage. That's how database-as-a-service (DBaaS) can help. You can limit the number of technologies and still be flexible.
Being able to analyze data in real-time will be a very hot topic for sure in near future. Not only for IoT-related tasks but as a general approach to user-to-machine or machine-to-machine interaction. From product recommendations to fraud detection alarms, a lot of stuff would be perfect if it could happen in real time. Now, with Azure Event Hubs and Stream Analytics, it’s possible. In this session, Davide will demonstrate how to use Event Hubs to quickly ingest new real-time data and Stream Analytics to query on-the-fly data, in order to do a real-time analysis of what’s happening right now.
This is a run-through at a 200 level of the Microsoft Azure Big Data Analytics for the Cloud data platform based on the Cortana Intelligence Suite offerings.
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Building a Real-Time Analytics Application with Apache Pulsar and Apache PinotAltinity Ltd
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While the demands for real-time analytics are growing in leaps and bounds, the analytics software must rely on streaming platforms for ingesting high volumes of data that's traveling in lightning speed down the pipeline. We will take a look at 2 powerful open source Apache platforms: Pulsar and Pinot, that work hand-in-hand together to deliver the analytical results which bring great value to your systems.
Presenters: Mary Grygleski - Streaming Developer Advocate &
Mark Needham - Developer Relations Engineer at StarTree
Note: This webinar will be recorded and later posted on our Webinar page (https://altinity.com/webinarspage/) or Altinity official Youtube channel (https://www.youtube.com/@Altinity).
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You’ve probably seen some cool data visualizations, and perhaps daydreamed of the day your organization’s data would be as easily computable. You’re not alone, many enterprises are falling behind the Big Data bandwagon and don’t all have clear direction to optimize their use of enterprise data as part of their cloud strategy.
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Have the message received by managers and peers along with a test email for review
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Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
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4. BIG DATA
• With IOT and business processes, lots of data is being collected
• Separation of concerns
• Process the data on the Server as much as possible
• Client computers should do as little work as possible.
• Services and Event Queues are good Architectures to explore
5.
6. MAP / REDUCE
• MAP – Group, Sort and Filter.
• Take all of the stock trades and split them out by company,
date or time
• Can be massively parallelized.
• Reduce – Functions on each groups.
• Examples are Counts, Sums and Averages.
11. BUSINESS REQUIREMENT
MAKE A BAR CHART
• Now that we have all the data separated out …
• Your Client wants to see it in a Bar Chart.
• Options:
• Generate Chart server side and Embed PDF
• Plain old HTML and CSS
• D3
• And more …
13. D3.JS
D3.js is a JavaScript library for manipulating documents based on data. D3 helps you
bring data to life using HTML, SVG, and CSS. D3’s emphasis on web standards gives
you the full capabilities of modern browsers without tying yourself to a proprietary
framework, combining powerful visualization components and a data-driven approach
to DOM manipulation.
• Written by Mike Bostock
http://d3js.org/
21. DC.JS
dc.js - Dimensional Charting Javascript Library
dc.js is a javascript charting library with native crossfilter support and allowing highly efficient
exploration on large multi-dimensional dataset (inspired by crossfilter's demo).
It leverages d3 engine to render charts in css friendly svg format. Charts rendered using dc.js
are naturally data driven and reactive therefore providing instant feedback on user's
interaction. The main objective of this project is to provide an easy yet powerful javascript
library which can be utilized to perform data visualization and analysis in browser as well as on
mobile device.
https://dc-js.github.io/dc.js/
• Fluent interface – Be careful of return type and order.
• Great for Dashboards
22. CROSS FILTER
Crossfilter is a JavaScript library for exploring large multivariate datasets in the
browser. Crossfilter supports extremely fast (<30ms) interaction with
coordinated views, even with datasets containing a million or more records; we
built it to power analytics for Square Register, allowing merchants to slice and
dice their payment history fluidly.
http://square.github.io/crossfilter/
23. CROSS FILTER
A Javascript Map / Reduce framework.
Steps for using Cross Filter
Create Indexes var ndx = crossfilter(data);
var all = ndx.groupAll();
Create Dimensions var dateDimension = ndx.dimension(function (d) { return d.date; });
Create Groups var dayWebGroup = dayDimension.group().reduceSum(function (d) { return
d.web; });
Use Groups on the charts stocksChart
.dimension(dayDimension)
.group(reduceGroup, "TV Spots")
25. DATATABLES
DataTables Table plug-in for jQuery
https://datatables.net/
DataTables is a plug-in for the jQuery Javascript library.
It is a highly flexible tool, based upon the foundations
of progressive enhancement, and will add advanced
interaction controls to any HTML table.
• Highly configurable JavaScript library for
displaying data in tables.
26. CONCLUSION
All Open Source – Still cant believe these tools are free.
Easy entry to building Dashboards.
It is still tough, but lots of help available online.
27. THANKS FOR LISTENING
Covered: d3.js, dc.js, crossfilter.js,
moment.js, datatables.net
Contact Info: Doug.Mair@gmail.com
@doug_mair
Feel free to ask Questions?
Editor's Notes
We can tell this is not random data There's a structure hereWhat does this resemble? Brain? Universe?It's a treasure trove of info, but not discoverable or explorable.
How do we get meaning out of it?
Often the data we have in Raw form is useless to our usersWe have to coalesce and massage the data to get at what is vitalThis is where the secret sauce and IP of companies is built
Found this on the Internet
Funny, yet accurate example of Map ReduceWalk through each step
This example is based on daily stock results Rolled up to provide monthly stats
Notice multiple Reduction functions here.Compare the size of the data before and after
Question: How can we tell which Company had the highest stock value for a monthQuestion: How can we tell which Day had the most activityAnswer: We can't because the data has been lost in the reduce
This is what makes developing hard and keeps us in businessIt's important to spend time figuring outWhat details the customer needWhich details get in the wayIteration of datasets is importantArchitect your data operations for change and growthArchitect your data Visuals for change too
You get a napkin with your requirements Document drawn on it.
How can we do this?
Switch to Example 1
Switch to Example 2
Shows redoing this with D3
Select – Enter - Exit
D3 works within the DOM Doesn't replace the DOM Similar concepts to jQuery
Mike Bostock started it while working at New York Times
Release in 2011.
Strong Open Source Community.
Here are examples of what D3 can do. Remember I said it was community supported Scroll through the items
Switch to Example 2.1 then 2.2
Lets use some of this power in our Bar Chart
Switch to Example 3
Code size is starting to grow. Can we refactor?
DC.js can help. Built on top of D3.js.
Switch to Example 4-DC-Bar-chart.html
Cool, much fewer lines of code.
Guess what, a new napkin appears …
Switch to 5-D3-Line-chart.html
How does interaction happen?
Switch to 6-D3-Dashboard.html
Show amount of CUSTOM code to add each chart.