Creating a Data-Driven Organization: Practical Advice from by Carl Anderson

Posted by

By Carl Anderson

What do you want to develop into a data-driven association? way over having massive information or a crack group of unicorn facts scientists, it calls for setting up a good, deeply-ingrained facts tradition. This functional publication indicates you ways precise data-drivenness contains approaches that require real buy-in throughout your organization, from analysts and administration to the C-Suite and the board. via interviews and examples from info scientists and analytics leaders in quite a few industries, writer Carl Anderson explains the analytics worth chain you want to undertake while construction predictive enterprise models—from info assortment and research to the insights and management that force concrete activities. you will study what works and what does not, and why making a data-driven tradition all through your company is vital.

Show description

Read Online or Download Creating a Data-Driven Organization: Practical Advice from the Trenches PDF

Similar data modeling & design books

IP Routing Fundamentals

A finished ntroduction to routing ideas and protocols in IP networks. * entire assessment of the operational mechanics of modern-day best routing protocols, together with IGRP, EIGRP, OSPF, RIP, and RIP-2 * distinctive clarification of IP addressing, together with classful and classless addresses, subnetting, supernetting, Classless Interdomain Routing (CIDR), and Variable size Subnet mask (VLSM) * Side-by-side comparisons of assorted LAN segmentation applied sciences, together with bridges, switches, and routers * Exploration of ways routers are used to construct extensive quarter networks * exam of the way forward for routing, together with IPv6, subsequent new release routing protocols, host-based routing, and IP SwitchingIP Routing basics is the definitive creation to routing in IP networks.

Beautiful Data

During this insightful ebook, youll research from the simplest info practitioners within the box simply how wide-ranging -- and lovely -- operating with facts may be. subscribe to 39 participants as they clarify how they constructed easy and stylish ideas on tasks starting from the Mars lander to a Radiohead video. With appealing facts, you are going to: discover the possibilities and demanding situations thinking about operating with the gigantic variety of datasets made to be had by means of the net the right way to visualize developments in city crime, utilizing maps and information mashups become aware of the demanding situations of designing an information processing procedure that works in the constraints of house shuttle learn the way crowdsourcing and transparency have mixed to strengthen the kingdom of drug examine know how new facts can instantly set off indicators whilst it suits or overlaps pre-existing information find out about the big infrastructure required to create, trap, and approach DNA info Thats purely small pattern of what youll locate in attractive facts.

Metaheuristics

Metaheuristics show fascinating homes like simplicity, effortless parallelizability, and prepared applicability to varieties of optimization difficulties. After a finished creation to the sphere, the contributed chapters during this ebook comprise reasons of the most metaheuristics concepts, together with simulated annealing, tabu seek, evolutionary algorithms, synthetic ants, and particle swarms, through chapters that display their purposes to difficulties equivalent to multiobjective optimization, logistics, car routing, and air site visitors administration.

Additional info for Creating a Data-Driven Organization: Practical Advice from the Trenches

Sample text

In one, they weigh the patients with their shoes on, in the other with shoes off. Clear protocols and training are needed to fix these types of issues. Just like any experiment, you need to try to control and standardize as much of the process as possible so that the data stands the best chance of being usable, reliable, and compa‐ rable. Data Entry When data is generated manually—such as the nurses measuring patients’ weights—it has to be recorded, ultimately in some sort of computer. Despite the promise of paperless offices, data is still far too often recorded on paper forms as an intermediate step before it is entered into a computer.

Martens, and F. ” Big Data 1, no. 4 (2013): 215–226. , February 6, 2001. info | 43 Velocity How much data you need to process per unit time. Imagine sampling Twitter data during a presidential debate to provide current sentiment. You have to not only process a huge amount of information, but do so at a rapid clip to be able to provide some real-time sense of how the nation is feeling about the remarks during the debate. Large-scale, real-time processing is complex and costly. ) Even organizations that collect a huge amount—Facebook, Google, and yes, the NSA, too—didn’t make it happen overnight.

Data Generation Data generation is the most upstream source of issues and can arise from errors in hardware (sensors), software (bugs), and wetware (humans). In hardware, sensors may be miscalibrated or uncalibrated, which can result in inaccurate readings. For instance, a temperature sensor might be reading high: it says 95°F when in reality it is only 93°F. That may be easy to fix: where possible, calibrate it against some source of truth, such as another trusted sensor or meter, during setup.

Download PDF sample

Rated 4.79 of 5 – based on 13 votes