One Article Review
| Source |  ProofPoint |
|---|---|
| Identifiant | 8527203 |
| Date de publication | 2024-06-28 09:54:24 (vue: 2024-06-28 14:06:36) |
| Titre | 3 façons dont la bonne visualisation des données aide à découvrir les informations sur la découverte électronique 3 Ways That Good Data Visualization Helps Uncover E-Discovery Insights |
| Texte | In a recent eDiscoveryToday article, a statistic caught my attention: The human brain “processes images 60,000 times faster than text, and 90% of the information transmitted to the brain is visual.” The implication was that “data visualization is an effective way to enhance attorney insights and decision-making in eDiscovery.” This inspired me to write a blog post that connects key features built into Proofpoint Discover to the way the human brain works. Here, I\'ll detail three unique data visualizations that help our clients speed up time to e-discovery insights and more. 1: Uncovering communication patterns with the “Network with List” view To better illustrate the value of our data visualization features, let\'s look at the e-discovery example below. In my demo archive sandbox, I\'ve archived 377,448 items across various source data types, from email to collaboration platforms to social media. If I search across the entire archive for anything that contains the words “confidential, sensitive, proprietary or internal,” I get in return 3,684 pages with over 55,259 results, as shown below. The Proofpoint Archive search feature, showing results. I could manually review this simple list of 55,259 results for relevancy (!). Or I could use data visualizations to speed up how I uncover patterns, items of interest and other insights. Let\'s change how I view the results from “List” to “Network with List.” That immediately sheds new light on communication patterns that could warrant further investigation. And there\'s no waiting to process or generate reports. This is simply a change in how to view the results, and it happens instantly. The Network with List view highlights top senders by activity within the search results, as shown below. Note that you can scroll your mouse over different top senders to identify their unique connections. You\'ll also see senders that are potentially not relevant, which you can easily exclude from the results. The Proofpoint Archive data visualization feature helps uncover patterns. 2: Identifying communication spikes with the “Timeline with List” view The Timeline with List view is another data visualization. But instead of examining communication connections as we did with the Network with List view, we\'re exposing bursts of communication that happen over a given period. These so-called “spikes” could be another set of communication patterns that warrant further investigation. Similarly, if you have no data for a potentially relevant date or series of dates, then you could address that early in your investigation. Using our same e-discovery example, let\'s change the view from “Network with List” to “Timeline with List.” Like before, this happens instantly, because we\'re just changing how to view search results. No additional processing is required. In the screenshot below, you can see that the visual changes from a network pie chart to a timeline bar chart, illustrating the volume of messages per year from the search results. Proofpoint Archive uses a “Timeline with List” view to uncover communication spikes. In our example, the year 2022 appears to have the most archived messages of potential interest. To investigate that further, you can click on the 2022 segment of the bar chart, which shifts the chart to a more granular view of search results per month in 2022. The results show that October was the most active month in 2022 in terms of volume of messages. Click on the October segment of the bar chart, and the graphic shifts to a new chart that displays activity in days over the course of October 2022, as shown below. Clicking on the bar chart in Proofpoint Archive provides a more granular view of results. You may not realize it, but you\'re filtering data with this exercise. You\'ve gone from 55,259 items in your original search to 3,181 i |
| Notes | ★★★ |
| Envoyé | Oui |
| Condensat | 000 123 181 2022 259 377 448 684 725 about across active activity add addition additional address administrator afraid all already also analytics analytics another anything appears archive archive archived are article aside asked assess assisted attention: attorney automate bar because been before begrudgingly behest below better biggest blog brain built bursts but called can capture case caught change changes changing chart classes click clicking clients collaboration communication compliance complimentary connections connects contains could course criteria data date dates days decision defined demo department derived desired detail did different discover discover discovery displays download early easily easy ediscovery ediscoverytoday effective email end enhance entire even ever examining example exclude exercise exposing faster fear feature features filtering filters finding format friends from further generate get given gone good granular graphic had happen happens have having haystack help helps here highlighted highlights how human identify identifying ifs” illustrate illustrating images immediately impact implication includes includes: info information initial insights inspired instantly instead intelligent interest internal internal” investigate investigation items just key know learn least legal let life light like list list” long longer look making management manually may media message messages month more most mouse network new not note number october ongoing only original other over page pages part patrol patterns pdf per period pie platforms popular portfolio post potential potentially process processing proof proofpoint proprietary provides query real realize recent reduced relevancy relevant remember remove removing report reports requests required rerun respective results return review run same sandbox schedule screenshot scroll search searches seconds see segment senders sensitive sentences series set sheds shifts show showed showing shown shows similarly simple simply social source specific specified speed spikes statistic such supervision suspect tags tar technology term terms text than then there these three time timeline times took top track transmitted type types uncover uncovering understand unequivocally unique use useful uses using value various view view view visit visual visualization visualizations volume waiting warrant way ways when which will within without words works write year yielded you your “confidential “data “haystacks” “internal” “list” “needle “network “processes “spikes” “timeline “what ” |
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