I took my writing on the road last night to meet up with some fellow NaNoers. I love meeting other writers. It must me feel, well not so weird in my quest to getting published. Most people who blog about writing are published writers or have gotten that YES from an agent. Me ~ not so much. I’m still one of those writers who is wallowing in the muck and mud trying to get someone to notice my work. Have I mentioned that querying sucks.

Back to NaNo. It has been an experience. Writing all the time with that deadline looming over my head constantly taunting me has been at times trying and other times exhilarating(that’s when you lose control of the words and they just spill out onto the page) – oh AND the words actually make sense and move the story forward. Gawd, that’s awesome! The past few days I’ve read plenty of blogs where the NaNoer is throwing in the towel. Why toss the towel when it’s not even Nov. 30th? Let me tell you my story is no where near complete but dammit I’m going to make it to 50k. Too bad for me the story will not be finished at 50k so I must push forward to oh I don’t know somewhere between 85,000 to 90,000. A lot of paranormal romance publishing houses require the story be between 80k-100k. All these f*cking guidelines can drive a writer mad. I think the story should dictate how long it should be, but what do I know I’m not published….YET!  Bahahahaha

Dear Doctor Query:

Peter Grant had the good sense to retire from his stint as a Marine on permanent loan to the CIA while all his parts were still in working order. Fifteen years as the pointy end of Uncle Sam’s big stick earned Grant the right to a quiet life.

Then an old friend calls in a chit, asks a simple favor. Since Grant already has plans to visit Tibet, all he has to do is deliver a letter when he gets there. The recipient? A mole. A high-ranking officer in China’s People’s Liberation Army, commander of a top-secret military facility outside Lhasa.

Based on an intelligence officer’s assessment, Grant expects to find a self-important, avaricious traitor who’s lost his nerve. Instead, he meets Colonel Sun, a determined, principled man caught in the closing jaws of a State Security investigation. Sun requests exfiltration, a move that would threaten the existence of the Tibetan network.

Grant finds himself sucked into the vortex that swirls around clandestine operations gone bad. A State Security officer dogs the colonel’s steps, half a world away Chinese spies relentlessly dig for the truth, and the carefully woven shroud of subterfuge that protects the Tibetan underground begins to unravel. In the scramble to protect networks, operatives, and secrets, the interests of nations threaten to grind the Chinese agent under the wheel of necessity.

But, Grant doesn’t have to let it happen. He doesn’t work for the CIA anymore.

Deep in hostile territory, operating naked on the remote Tibetan plateau, Grant takes a risky gamble. He plots Colonel Sun’s escape, a hell-for-leather race to freedom.

The simple favor just got complicated.

I am seeking representation for SKY FUNERAL, a completed 90,000 word spy thriller, the first in a planned series. I have a master’s degree in aerospace engineering and a fourteen-year career in the defense industry. I’ve been a member of Pikes Peak Writers, Colorado Springs Fiction Writer’s Group, and Valencia Critique Group, and have attended numerous writing seminars, conferences, and classes.

This is very good.

You have given us a sense of urgency, and your voice has authority.  The query and the subject matter fit together, and your life experience makes a convincing argument that you could tell this story.  As a reader, I feel as though I would be in good hands with you.

The only thing I would do is tighten it up.  Take your seven paragraphs and try to turn them into three or four. Brevity is strength.

Then send it out!

That is all.

Doctor Query

ใน PDO query 2 ครั้งติดกันอาจจะเจ๊ง ถ้าหากว่า fetch ข้อมูลออกมาไม่หมด (ตามคู่มือ) แต่ก็มีท่าแก้คือ เรียก closeCursor ก่อน

You may have seen last week when I announced that I had signed an agency contract with Kim Lionetti at Bookends. Well, I promised to post some thoughts about the process, so here they are.

Finding an agent is, as we all know, not an easy path. Here’s my story and what I learned.

I started querying 16 months ago with my first book. I made the standard newbie mistake of sending it out when I thought it was ready. Of course, I didn’t realize I was making the mistake. I’d revised and edited it. I’d worked with a CP and beta readers. I’d grown and pushed my story. But it wasn’t enough. I blew through about 50 agents who my sorting process had said were a good match before I realized this. A couple agents gave me amazing notes on how to better my book. Another 4 months of work and I realized I had a YA Fantasy novel I loved. No longer that first love like when you’re young and think this MUST be it, but a mature love of someone who had seen young love and learned from it.

And I was also out of agents to query who would fit in the Great Match category.

Last November I took a much needed break from the intense world of my fantasy and decided to try Nano. Only, it went a little too well. I wrote Secret Girlfriend (a Rom Com’y type story) in 11 days and surprised myself by loving every minute of it. Secret Girlfriend is the exact opposite of Markbearer. It’s lighter, fewer story lines, fewer themes, only one world, fewer characters and funny (good lord, I hope it’s funny). Every thought in my head was to just call it a palate cleansing exercise and get back to my fantasy world.

Flash Forward to this summer. The fantasy was done-done and I did an ROI on writing book two of such a huge undertaking without being able to query it since it wouldn’t be a standalone. (I did take into consideration the threats from the people who had read book 1…but, alas, they lost). On a whim, I opened Secret Girlfriend and ran through it. Wow. How surprised was I to see it was pretty darn clean? I started sending my weekly chapters to my CP and was surprised to find out she thought it was clean too.

The beta readers read through it quickly too and then Gwen Hayes forced me into querying. Not only that, but her husband got in on it: If you send five queries today, I’ll bake you a pie. (I’d just like to say, I blame him 100% for the weight I gained during this process.)

This is where I stop the story to discuss the actual query process.

I’d learned a lot querying my first book. I learned when to listen to what They say and when not to. For example. I made a list of 20 agents I would love love love to have. TWENTY??? Yes. Twenty. The process the first time taught me that the idea of a “dream agent” is not only wrong, but it’s not healthy. What do you do when that person rejects you off a query without even looking at your work? They may not be interested in you for several reasons. They may not actually be your dream agent. But how would you know that? You typically haven’t met them, spoken with them or seen anything other than their online presence. The last round I found that two of my “dream agents” were actually people who would be a horrible match for me (and so visa versa).  Also, waiting for a small number puts your entire career on hold. Would you only send your resume out to one employer at a time if you were jobless?

If you didn’t see my post on how I researched, organized and sorted agents, check it out HERE. It explains that part of the process very clearly.

So, I removed some agents and added others then started the process for book 2. After Mr. Hayes bribed me with pie, I sent out a minimum of 2 queries a day on business days. I logged them all on querytracker.net (Go get it now if you don’t have it) and then I put it aside. I wasn’t going to think about them for 2 months.

The plan was to look at the remaining agents on my list at that time and sort them into groups of five to send out as rejections came in. Only, that’s not how book 2 went. Book 2 went something like this:

• Mr. Gwen bribes me to send out queries
• Queries get surprising number of requests surprisingly quickly
• Partial requests turn into fast (again surprising) full requests
• Full request turns into an offer
• One offer turns into several
• About a month has gone by since Mr. Gwen’s bribes put a disgusting amount of fat in my body (when I say disgusting, I mean the best tasting stuff on the planet)

I think we can all admit, this is not the normal time frame…and hopefully not the normal amount of weight put on in a month…

Obviously, a lot went on during the week where I got the offers. But another thing I think we can all agree on is how long this post is! So, I’ll be posting later about what I actually learned during that week.

Data Warehouse adalah relasional database dengan desain tertentu yang memudahkan Query dan Analisis.

Pada umumnya Data Warehouse berisi data sejarah yang diturunkan dari data transaksi dan beberapa data dari sumber data yang lain.

Dengan Data Warehouse maka Organisasi bisa mendapatkan data yang sudah terkonsolidasi dari berbagai sumber data.

William Harvey Inmon atau biasa dipanggil Bill Inmon pada tahun 1991 dalam bukunya “Building the Data Warehouse”
mendefinisikan Data Warehouse sbb.:

“A data warehouse is a subject-oriented, integrated,
timevariant, and nonvolatile collection of data
in support of management’s decision-making
process.”

Subject-oriented:
- Data di kumpulkan berdasarkan subjek utama, misalnya
Customer, Product atau Sales.
- Data Model dan analisa diutamakan untuk pengambil
keputusan bukan untuk proses transaksi sehari-hari.
- Menyediakan cara yang sederhana dan ringkas untuk
menampilkan data sekitar subjek tertentu dengan cara
mengeluarkan data yang tidak berguna dalam proses
pengambilan keputusan.

Integrated:
- Dibangun dari integrasi berbagai macam sumber data
misalnya Relational Database, Flat Files, Online
Tansaction record, dsb.
- Menggunakan teknologi Data Cleansing dan Data
Integration. Tujuannya:
- Memastikan konsistensi Naming Convention,
Encoding Structure, Ukuran attributes. dsb.
diantara sumber data yang berbeda-beda.
- Ketika data dimasukkan ke Data
Warehouse, data tesebut telah dikonversikan.

Time Variant:
- Rentang waktu data untuk Data Warehouse pasti lebih
panjang jika dibandingkan dengan sistem operasional
- Data Sistim Operasional : Data saat ini
- Data Data Warehouse : Menyediakan informasi
dari perspektif sejarah misal 5 s/d 10 tahun
- Setiap struktur Key dalam Data Warehouse selalu
mengandung elemen Time secara implisit atau explisit
- Namun pada Key data operasional mungkin tidak
mengandung elemen Time.

Non Volatile:
- Artinya begitu data masuk ke Data Warehouse
seharusnya Data tidak boleh berubah lagi.
- Secara fisik data pada Data Warehouse disimpan
terpisah dari operasional sistem.
- Operasi Update tidak pernah terjadi pada lingkungan
data Warehouse, karena
- Tidak perlu melakukan proses transaksi, Recovery,
dan mekanisme kontrol proses simultan.
- Hanya memerlukan dua operasi proses Data yaitu
Data Loading dan Data Retrieving.

Elemen-elemen dasar Data Warehouse

Source System
Operasional sistem yang berfungsi mencatat transaksi dari
suatu bisnis. Source System biasa disebut juga sebagai
Legacy System.

Data Staging Area
Tempat penyimpanan data sementara, untuk melakukan
proses Clean, Transform, Combine, Deduplicate,
Household, archive, dan menyiapkan sumber data untuk
digunakan Data Warehouse.

Staging Area tidak diperuntukkan sebagai sumber data
untuk reporting karena datanya masih kotor dan bersifat
sementara.

Presentation Server
Target mesin yang secara fisik adalah mesin dimana data
dari Data Warehouse di organisasikan dan disimpan untuk
dilakukan query oleh End User, Reporting dan aplikasi yang
lain. Disini data disimpan dengan framework Dimmensional.

Jika menggunakan Relational Database maka tabel akan
diorganisasikan dalam bentuk Star-Schema, namun
jika tidak menggunakan Relational Database maka akan
disimpan dalam bentuk OLAP.
(mengenai OLAP akan dibahas pada sesi tersendiri)

Dimensional Model
Data Modeling yang khusus dipakai pada Data Warehouse,
sebagai alternatif lain dari E/R Modeling yang biasanya
dipakai pada sistem transaksional.
(mengenai Dimensional Modeling, akan dibahas pada sesi
tersendiri)

Business Process
Dalam terminologi disini bukanlah Business Process seperti
pada transaksional sistem, tetapi lebih tepat maksudnya
adalah mengelompokkan sumber data menurut kesamaan
temanya. Misalnya Finance, Marketing, Production. etc.

Nantinya setiap Business Process akan diimplementasikan
sebagai Data Marts.

Data Mart
Potongan secara logika dari Data Warehouse secara
keseluruhan.

Data Mart bisa juga dilihat sebagai potongan secara logika
dari data Warehouse terhadap suatu Business Process
tertentu.
(mengenai Data Mart, akan dibahas pada sesi tersendiri)

Data Warehouse
Adalah sumber data yang bisa di Query dalam suatu
perusahaan. Sebenarnya Data Warehouse adalah
gabungan dari beberapa Data Marts.

Operational Data Store
Pada awalnya ODS adalah titik integrasi dari berbagai
operasional sistem. Karena ODS juga mendukung access
operasional dan bisa di update maka ODS seharusnya
ditempatkan diluar Data Warehouse.

Pada akhirnya fungsi ODS juga berkembang menjadi
semacam Desicision Support karena ODS mengandung
detail data yang telah terintegrasi dari berbagai sumber
Data.
(mengenai ODS, akan dibahas pada sesi tersendiri)

OLAP
Disebut juga sebagai Multidimensional Database (MDDB).
OLAP sengaja dirancang untuk memudahkan dan
mempercepat query yang dilakukan pada MDDB.

Karakteristik dan sifat OLAP sangat berbeda dengan OLTP
karena memang mempunyai tugas dan fungsi yang
berbeda.

ROLAP
Relational OLAP.

MOLAP
Multidimensional OLAP
(mengenai OLAP, ROLAP dan MOLAP, akan dibahas pada
sesi tersendiri)

End User Application
Sekumpulan Tool yang bisa melakukan Query, Analisa
Data, dan menampilkan informasi untuk mendukung
kepentingan Bisnis.

Paling tidak Tool ini juga dilengkapi dengan kemampuan
untuk akses Data, fungsi Spreatsheet, fungsi grafik, dan
ada fasilitas untuk menampilkan prompt dan
menyederhanakan tampilan screen pada End User.

End User Data Access Tool
Sebagai Client dari Data Warehouse. Pada Relational Data
Warehouse, Client dapat mengirimkan SQL Request
ke Server.

Secepatnya End User Data Access Tool akan selesai pada
SQL Session dan kembali untuk menampilkan pada screen
Data dari suatu Report, Grafik, atau yang lebih tinggi
seperti form suatu analisa pada User.

End User Data Access Tool dapat saja sederhana seperti
Ad-Hoc Query Tool atau bisa juga bisa komplex
seperti Data Mining yang canggih atau aplikasi modeling.

Ad-Hoc Query Tool
End User Data Access Tool yang dibuat khusus sehingga
memungkinkan User untuk membuat Query sendiri secara
langsung dengan cara memanipulasi Relational Tables dan
Join-join nya.

Dipasaran biasanya Ad-Hoc Query Tool dipaket menjadi
satu dengan Reporting Tool.

Modeling Application
Data Warehouse Client yang canggih dengan kemampuan
analytic yang dapat merubah bentuk atau menjadikan
intisari dari output Data Warehouse.

Modeling ini termasuk didalamnya adalah:
- Forecasting Model, yang berusaha memperkirakan masa
depan
- Behaviour Scoring Model, yang dapat mengklasifikasikan
perilaku belanja Customer
- Allocation Model, yang mengambil data Cost dari Data
Warehouse lalu membagikan Cost tersebut ke semua
poduct Group atau Customer Group.
- Terutama Data Mining Tools.

Meta Data
Semua informasi dalam lingkungan Data Warehouse namun
bukan data itu sendiri, Misalnya informasi mengenai
asal data source dari aplikasi apa, tabel apa, field apa,
formula bisnis bagaimana, dsb. Meta Data perlu dibuatkan
Catalog, diberi Version Stamp, di dokumentasikan dan di
backup.

Beberapa ETL Tool dipasaran ada yang sudah dilengkapi
Meta Data management.

Demikian elemen dasar dari Data Warehouse, masih banyak komponen yang nanti akan di jelaskan pada sesi berikutnya.

Reff:
Kimball, Ralph, 1998, The Data Warehouse Lifecycle Toolkit, Jhon Wiley & Sons, Inc.

Boa noite pessoas!

No blog do Rogério, encontrei um ótimo algoritmo de validação de CNPJ e CPF para ORACLE, para que ninguém tenha que ficar transitando de ‘PL\SQL’ para ‘T-SQL’, já realizei este trabalho e vou detalhar um pouco o funcionamento deste algoritmo.

Primeiro precisamos de um CNPJ ou CPF para validar, assim identifiquei um que estava “vagando” na internet.

Ok, tenho o CNPJ/CPF para validar, mas tenho que remover os caracteres não numéricos, desta forma utilizarei a função SOMENTE_NUMEROS que desenvolvi para o artigo anterior:

A primeira valiação verifica se a quantidade de caracteres é de um CPF ou de um CNPJ

Em sequida, defino quatro variáveis que serão utilizadas para a validação dos digitos verificadores do CNPJ e CPF.

Também há outras variáveis a serem utilizadas durante a operação.

As variáveis DIGITO1 e DIGITO2 armazenarão os digitos verificadores do CNPJ/CPF.

Feito isso, determino um laço de repetição para dois loops, um para cada digito.

 Determino os valores inicias das variáveis de validação.

Agora, aplico o algoritmo para gerar cada um dos digitos verificadores.

Identifico qual dos digitos verificadores foi gerado e prossigo para o próximo digito no laço de repetição.

Por fim, verifico se os digitos gerados têm o mesmo valor dos presente no CNPJ/CPF.

Para o próximo artigo, ainda estou estudando uma forma interessante de trabalhar com máscaras e CTE.

Disponíveis para download:

Função SOMENTE_NUMEROS (com CTE):
http://www.4shared.com/file/152602089/d1b4b224/SOMENTE_NUMEROS_-_CTE_-_Func.html

Função SOMENTE_NUMEROS (com WHILE):
http://www.4shared.com/file/152602109/18af521b/SOMENTE_NUMEROS_-_WHILE_-_Func.html

Função VALIDA_CPF_CNPJ:
http://www.4shared.com/file/152602115/8022f71/VALIDA_CPF_CNPJ_-_Func.html

Artigos relacionados:

Blog do Rogério – Validação CNPJ/CPF com PL/SQL
http://blogdozunga.blogspot.com/2009/02/precisava-de-uma-rotina-para-validar.html

FUNÇÕES: Somente Números (com CTE)
http://sqlfromhell.wordpress.com/2009/11/18/somente-numeros-com-cte/

FUNÇÕES: Somente Números (com WHILE)
http://sqlfromhell.wordpress.com/2009/11/17/somente-numeros-com-while/

Query yang gw ketemuin tadi siang pas lagi bersih-bersih database. Ini cuman “satu query” lho. Bloody hell… liatnya aja udah eneg -_-!. Kayanya ini sementara bakalan menjadi query terpanjang yang gw temuin semenjak in charge di permbuatan sistem 2010 NextG. Kali aja besok-besok dapet query yang lebih puanjaaaang lagi… hohoho….

SELECT t.sales_number, sum(t.badan_pusat_pengelolaan_data_asuransi_nasional) AS badan_pusat_pengelolaan_data_asuransi_nasional, sum(t.combined_non_marine_surplus_treaty) AS combined_non_marine_surplus_treaty, sum(t.fire_statistical_cession_reinsurance_treaty__bppdan) AS fire_statistical_cession_reinsurance_treaty__bppdan, sum(t.indonesian_standard_earthquake_reinsurance__maipark) AS indonesian_standard_earthquake_reinsurance__maipark, sum(t.pt_asuransi_maipark_indonesia) AS pt_asuransi_maipark_indonesia, sum(t.non_marine_surplus_reinsurance_agreement) AS non_marine_surplus_reinsurance_agreement, sum(t.non_marine_surplus_reinsurance_agreement__extention_of_2008) AS non_marine_surplus_reinsurance_agreement__extention_of_2008, sum(t.marine_cargo_excess_of_loss_reinsurance_contract) AS marine_cargo_excess_of_loss_reinsurance_contract, sum(t.marinecargoxolreinsurancecontractextentionof2008) AS marinecargoxolreinsurancecontractextentionof2008, sum(t.non_marine_quota_share_reinsurance_agreement) AS non_marine_quota_share_reinsurance_agreement, sum(t.non_marine_quota_share_reinsurance_agreement__extention_of_2007) AS non_marine_quota_share_reinsurance_agreement__extention_of_2007, sum(t.non_marine_quota_share_reinsurance_agreement__extention_of_2008) AS non_marine_quota_share_reinsurance_agreement__extention_of_2008, sum(t.riotsstrikesandmaliciousdamageandnaturalperilsxolra) AS riotsstrikesandmaliciousdamageandnaturalperilsxolra, sum(t.riotsstrikesandmaliciousdamageandnaturalperilsxolraextof2008) AS riotsstrikesandmaliciousdamageandnaturalperilsxolraextof2008, sum(t.riotsstrikesandmaliciousdamagexolra) AS riotsstrikesandmaliciousdamagexolra, sum(t.riotsstrikesandmaliciousdamagexolramainlayer) AS riotsstrikesandmaliciousdamagexolramainlayer, sum(t.riotsstrikesandmaliciousdamagexolramainlayerextentionof2008) AS riotsstrikesandmaliciousdamagexolramainlayerextentionof2008, sum(t.riskandcatastrophexolra) AS riskandcatastrophexolra, sum(t.riskandcatastrophexolraextentionof2008) AS riskandcatastrophexolraextentionof2008, sum(t.rsmdandnaturalperilsxolra) AS rsmdandnaturalperilsxolra, sum(t.terrorismandsabotagexolrasublayer) AS terrorismandsabotagexolrasublayer FROM (SELECT DISTINCT “maintenance”.reassraw.sales_number, “maintenance”.reassraw.treaty_type, “maintenance”.reassraw.treaty_name, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Badan Pusat Pengelolaan Data Asuransi Nasional’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END AS badan_pusat_pengelolaan_data_asuransi_nasional, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Combined non marine surplus treaty’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END AS combined_non_marine_surplus_treaty, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Fire statistical cession reinsurance treaty (BPPDAN)’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END AS fire_statistical_cession_reinsurance_treaty__bppdan, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Indonesian standard earthquake reinsurance (MAIPARK)’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END AS indonesian_standard_earthquake_reinsurance__maipark, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘PT. Asuransi MAIPARK Indonesia’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END AS pt_asuransi_maipark_indonesia, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Non Marine Surplus Reinsurance Agreement’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END AS non_marine_surplus_reinsurance_agreement, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Non Marine Surplus Reinsurance Agreement (Extention of 2008)’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END AS non_marine_surplus_reinsurance_agreement__extention_of_2008, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Marine Cargo Excess of Loss Reinsurance Contract’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END AS marine_cargo_excess_of_loss_reinsurance_contract, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Marine Cargo Excess of Loss Reinsurance Contract (Extention of 2008)’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END AS marinecargoxolreinsurancecontractextentionof2008, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Non Marine Quota Share Reinsurance Agreement’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END AS non_marine_quota_share_reinsurance_agreement, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Non Marine Quota Share Reinsurance Agreement ( Extention of 2007)’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END AS non_marine_quota_share_reinsurance_agreement__extention_of_2007, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Non Marine Quota Share Reinsurance Agreement (Extention of 2008)’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END AS non_marine_quota_share_reinsurance_agreement__extention_of_2008, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Riots, Strikes and Malicious Damage and Natural Perils Excess of Loss Reinsurance Agreement’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END AS riotsstrikesandmaliciousdamageandnaturalperilsxolra, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Riots, Strikes and Malicious Damage and Natural Perils Excess of Loss Reinsurance Agreement (Extention of 2008)’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END AS riotsstrikesandmaliciousdamageandnaturalperilsxolraextof2008, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Riots, Strikes and Malicious Damage Excess of Loss Reinsurance Agreement’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END AS riotsstrikesandmaliciousdamagexolra, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Riots, Strikes and Malicious Damage Excess of Loss Reinsurance Agreement (main layer)’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END AS riotsstrikesandmaliciousdamagexolramainlayer, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Riots, Strikes and Malicious Damage Excess of Loss Reinsurance Agreement (main layer) (Extention of 2008)’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END AS riotsstrikesandmaliciousdamagexolramainlayerextentionof2008, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Risk and Catastrophe Excess of Loss Reinsurance Agreement’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END AS riskandcatastrophexolra, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Risk and Catastrophe Excess of Loss Reinsurance Agreement (Extention of 2008)’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END AS riskandcatastrophexolraextentionof2008, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘RSMD and Natural Perils Excess of Loss Reinsurance Agreement’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END AS rsmdandnaturalperilsxolra, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Terrorism and Sabotage Excess of Loss Reinsurance Agreement (sub layer)’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END AS terrorismandsabotagexolrasublayer FROM “maintenance”.reassraw ORDER BY “maintenance”.reassraw.sales_number, “maintenance”.reassraw.treaty_type, “maintenance”.reassraw.treaty_name, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Badan Pusat Pengelolaan Data Asuransi Nasional’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Combined non marine surplus treaty’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Fire statistical cession reinsurance treaty (BPPDAN)’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Indonesian standard earthquake reinsurance (MAIPARK)’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘PT. Asuransi MAIPARK Indonesia’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Non Marine Surplus Reinsurance Agreement’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Non Marine Surplus Reinsurance Agreement (Extention of 2008)’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Marine Cargo Excess of Loss Reinsurance Contract’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Marine Cargo Excess of Loss Reinsurance Contract (Extention of 2008)’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Non Marine Quota Share Reinsurance Agreement’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Non Marine Quota Share Reinsurance Agreement ( Extention of 2007)’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Non Marine Quota Share Reinsurance Agreement (Extention of 2008)’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Riots, Strikes and Malicious Damage and Natural Perils Excess of Loss Reinsurance Agreement’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Riots, Strikes and Malicious Damage and Natural Perils Excess of Loss Reinsurance Agreement (Extention of 2008)’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Riots, Strikes and Malicious Damage Excess of Loss Reinsurance Agreement’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Riots, Strikes and Malicious Damage Excess of Loss Reinsurance Agreement (main layer)’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Riots, Strikes and Malicious Damage Excess of Loss Reinsurance Agreement (main layer) (Extention of 2008)’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Risk and Catastrophe Excess of Loss Reinsurance Agreement’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Risk and Catastrophe Excess of Loss Reinsurance Agreement (Extention of 2008)’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘RSMD and Natural Perils Excess of Loss Reinsurance Agreement’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END, CASE WHEN (“maintenance”.reassraw.treaty_name = ‘Terrorism and Sabotage Excess of Loss Reinsurance Agreement (sub layer)’::text) THEN “maintenance”.reassraw.a_rp ELSE (0)::numeric END) t GROUP BY t.sales_number;

i’ve heard some rumors about our department.  i just got back today, this morning. and banyak sekali news yang sedih. i’ll be devastated kalau sungguh ianya happen. i’ll be sad. i don’t think i can even accept it. i just wish.. semuanya salah. that kami akan ’selamat’. at least buat masa sekarang. i can’t afford to take any.. anything.. i’ll just be sad kalau sungguh ianya jadi…

i wonder. kalau la sungguh u’re so called orang besar. kenapa lah anda tidak berfikir sebelum buat keputusan. kenapa?

and sharon’s leaving to subang. and all my files are still with her. i dont know about my status here. i’m yet to be confirm. well half-ly i am. but the other half. i just cant say it yet.. why is this happening to me..

and another thing. amir also halfway leaving this dec..

why semua harus diberitahu today..

Boa noite pessoal!

Continuando o artigo anterior, vou demonstrar como recuperar somente os valores numéricos de um texto, agora com CTE. 

Para começar, tenho o mesmo cenário do artigo anterior, uma variável com um texto absurdo, da qual desejo somente retornar os valores numéricos. 

Como estou utilizando CTE, não tenho necessidade de muitas variáveis.

Mas ainda continuo a ter a necessidade das variáveis que delimitam o RANGE dos valores numéricos, no caso os ‘valores decimais’ dos caracteres 0 (zero) e 9 (nove):

Com a primeira CTE, realizo crio a relação de um a um dos caracteres do meu texto (um caractere por linha). Na segunda CTE, aplico a validação do RANGE de cada um dos caracteres relacionados na primeira CTE.

Por fim, utilizo uma query para concatenar os valores resultantes da segunda CTE, adicionando o HINT MAXRECURSION, para evitar que um texto com mais de 100 caracteres prejudique minha operação.

No próximo artigo trarei a validação de CPF e CNPJ em uma única operação (e de forma otimizada).

Disponíveis para download:

Função SOMENTE_NUMEROS (com CTE):
http://www.4shared.com/file/152602089/d1b4b224/SOMENTE_NUMEROS_-_CTE_-_Func.html

Função SOMENTE_NUMEROS (com WHILE):
http://www.4shared.com/file/152602109/18af521b/SOMENTE_NUMEROS_-_WHILE_-_Func.html

Artigos relacionados:

CTE – Introdução:
http://sqlfromhell.wordpress.com/2009/09/20/cte-introducao/

It appears that LINQ does not support a query that outputs multiple group by aggregate fields.  For example, there’s Min() and a Max() functions, so to get both min & max from a list, you seem to need to make 2 LINQ queries:

 var min = (from d in data select d).Min();

 var max = (from d in data select d).Max();

In SQL, the 2 values would pop out easily from a single query:

 Select min(d), max(d) from data

LINQ has all the power of SQL and works similarly, just the syntax is different.  To achieve this result we have to use a group by.  But we’ll be grouping by nothing, including all items in the set in a single bucket. I usually group by “1”, which makes a single grouping of all the elements (grouping by any single object will do the same):

 var minMax = from d in values

    group d by 1 into g

    select new { Min = g.Min(x => x),

     Max = g.Max(x => x) };

damn you access

Does ANYONE out there know how to use Microsoft Access???? Good God. That programme is so complicated. It doesn’t look complicated, cuz it looks just like any other MS Office tool, but geez man!

I’m trying to create a database for work, to keep track of Scientific Research Permit Applications, but it’s a lot harder than it sounds. I want to create it in such a way, that it can be queried to give us snapshots of certain information likeeee how many permits have been issued in the last 6 months, or where in The Bahamas research is going on, orrrr the nature of the ongoing research (ie: marine, geology, terrestrial, bla bla)

Anyway, it seems like I’m almost there, but the form I’m creating isn’t working properly. Sigh. So frustrating.

BI atau Business Intelligence yang telah tumbuh pesat dalam satu dasawarsa terakhir mempunyai arti yang luas.
Pada awalnya BI hanya menyangkut pada database Customer saja, namun sekarang telah meluas pada semua segi dari suatu bisnis.

Sebenarnya tujuan BI menyangkut dua hal penting:

- Data Integration, yang berarti menarik data dari berbagai sumber data yang terpisah-pisah dalam berbagai format data, dari berbagai Database lalu disimpan pada satu Database dan membuatnya dapat di access dengan mudah dengan cara yang seragam. Database ini biasa disebut dengan Data Warehouse.

– Analysing and Viewing, yang berarti menyediakan cara untuk menampilkan dan melakukan analisa data dengan cara yang baru dan menampilkan informasi yang sebelumnya tersembunyi. Aplikasi untuk keperluan ini biasa disebut dengan BI Application.

Tujuan tersebut telah dikembangkan selama bertahun-tahun. Awalnya tampak seperti alat untuk market research,  untuk mengentahui karakteristik Customer, untuk menemukan pola-pola dalam Pendapatan dan Keuntungan, atau untuk memahami perilaku Customer, namun saat ini tool yang sama juga dipakai untuk melihat berbagai aspek bisnis.

Istilah BI sendiri pertama kalinya diperkenalkan oleh Howard Dresner dari Gartner Group pada tahun 1989 dengan defenisi
sbb.:

“Business Intelligence is a set of concepts and methodologies to improve  decision-making in business through the use of facts and fact-based systems”

Menurutnya BI adalah sekumpulan konsep dan methodologi untuk meningkatkan pengambilan keputusan dalam bisnis dengan cara menggunakan fakta dan sistem yang berdasarkan fakta.

Bahan dasar dari BI adalah semua transaksi individu, dan data diambil dari berbagai sisi bisnis. Dengan BI setiap detail data bisa diambil namun akan disimpan dengan menggunakan struktur data yang baru sehingga detail tersebut dapat di access dari berbagai sudut pandang. Sehingga untuk setiap pertanyaan bisnis BI akan dapat memberikan jawaban secara tepat dan cepat.

BI akan memberikan sudut pandang bisnis dengan detail yang belum pernah ada sebelumnya. Hal itu dapat dicapai dengan cara merestrukturisasi informasi dengan tepat yang dibutuhkan oleh setiap fungsi kerja, apakah fungsi kerja tersebut adalah market research,
quality assurance, general management atau fungsi kerja yang lain.

Fungsi-fungsi BI yang lain adalah;

-BI memungkinkan pebisnis untuk melihat kinerja bisnisnya dari berbagai sudut pandang, tidak hanya dari sisi accounting belaka.
-Untuk mengetahui pola belanja customer
-Untuk mengungkap hubungan antara suatu kejadian dengan kinerja dagang.
-Untuk melihat dampak nyata dari suatu promosi selagi masih berlangsung.
-Untuk mengungkap penipuan dan pemborosan yang tak berguna.
-Untuk melihat suatu problem selagi dibenahi

Singkatnya, BI memungkinkan untuk memanfaatkan nilai yang ada secara detail

Teknologi apa saja yang digunakan BI?

ETL Tool:
Agar data dari berbagai sumber data dapat di access, maka diperlukan teknologi yang bisa connect ke berbagai Database di berbagai platform. Proses ini meliputi Collection, Cleansing, Extraction, Transformation, and Loading, Tool yang menyediakan fungsi-fungsi ini biasa disebut ETL Tool. Ada berbagai macam ETL tool yang tersedia di pasar, tersebar dngan bebagai kelebihan fungsi dengan harga yang beragam juga.

OLAP Engine:
Agar suatu data dapat dilihat dan di analisa dari berbagai sudut pandang, maka data tersebut perlu disimpan dengan struktur multi dimensi, atau yang disebut dengan Multidimensional database. Untuk  mempercepat query dan analisa maka semua relasi data perlu disimpan dalam group-group dari item-item data yang behubungan, disimpan juga Jumlah item yg berhubungan, dan agregasi dari kuantitas data yang  berhubungan. Semua fungsi ini akan ditangani oleh OLAP Engine.
(Lebih jauh mengenai OLAP akan dibahas pada sesi tersendiri)

Query Tool:
Setelah data disimpan dalam Multidimensional Database, untuk menampilkannya diperlukan tool khusus yang dapat melakukan
berbagai query multi dimensi. Tool ini dapat membuat rumusan query multi dimensi yang kompleks dengan cara yang sederhana
tool ini biasa disebut dengan Query Tool. Beberapa produk Query Tool dipasaran telah dilengkapi juga dengan OLAP Browser
bahkan ada yang di paket dengan Reporting Tool.

Reporting Tool:
Pada Multidimensional Database reporting tool yang dipakai juga harus bisa membaca data multi dimensi.
Pada umumnya Reporting Tool bisa dijalankan dengan cara visual desain dan sudah dilengkapi dengan OLAP Browser.
Report dapat diexport dalam berbagai format sperti format CSV,  PDF file atau PPT file untuk keperluan presentasi.
Beberpa Reporting Tool di pasaran bahkan ada yang dilengkapi dengan Distribution Utility dan Schedulling.

Dashboarding Tool:
Informasi yang disampaikan untuk para pengambil keputusan biasanya tidak ditampilkan dalam angka-angka dalam tabel,
namun dalam bentuk grafik-grafik interaktif untuk mempermudah dan mempercepat pengambilan keputusan. Tool yang mempunyai kemampuan ini disebut dengan Dashboarding Tool.
Dashboarding Tool dilengkapi dengan berbagai macam grafik seperti Bar Chart, Pie Chart, Gauge Chart, dll. baik 2D maupun 3D,

Disamping Tool utama yang sudah disebut diatas, sebenarnya masih ada beberapa tool lagi yang biasa dipakai baik oleh BI Developer ataupun oleh BI User. Mengenai hal ini akan dibahas disesi lain.

Reff:
Tiwana, Amrit, 2001. The Essential Guide to Knowledge Management, New York,USA, Prentice Hall
Kimbal, Ralp, 1996, The Data Warehouse Toolkit, New York-USA,  Jhon Wiley & Sons, Inc.

Hoje Eu e a Luciane enfrentamos um problema: Realizar um select em um campo datetime do MySql. Parece simples? Mas não foi!

Em nossas consultas sempre realizamos pesquisas no banco de dados com campos do tipo datetime, porém nunca enfrentamos a situação em que o resultado sempre vinha vazio sendo que temos dados em banco. Desta forma começamos a perguntar: Porque o aqua (nossa ferramenta para consultas à banco de dados) não traz o resultado?

Nosso select no aqua era o seguinte:

select * from tabela where campo_data = current_date

Bom, normalmente, para outras consultas esse comando sql funcionaria. Desta vez não foi bem assim.

Dando uma analisada no conteúdo da tabela no banco, identificamos as seguintes datas:

16/11/2009 11:39:00
16/11/2009 10:30:03

Desta forma, podemos identificar que, apesar de serem mesmas datas, o datetime permite gravação de hora, minuto e segundos. Essa foi a primeira pista.

A segundo pergunta foi: Como estão sendo gravados estes dados?

Identificamos que no PHP, na realização do insert em banco de dados, o programador pegou a data atual com o seguinte comando: “now”. Agora temos a segunda pista. O comando “now” do PHP traz a data atual, acompanhada de hora, minuto e segundos! Assim, quando era realizado insert em banco, era gravado a data com a hora atual, porém na busca estavamos utilizando apenas a data. O resultado do SQL era vazio pois a data era a mesma mas a hora não.

Como resolver?

A idéia inicial foi alterar a função PHP de ‘now’ para date(‘Y-m-d’). E deu certo!

Ao utilizar a função “date”, o PHP grava a data no campo, com a hora zerada. Desta forma a consulta sql desconsidera a hora para aquela linha, trazendo o registro. É isso!

Abraço.

Sending work to a publisher or a literary agent should be the culmination of hours of work polishing, and lovingly tending to your manuscript to make sure that it’s well-edited, and reading it is like gliding a hot knife through butter.

This is the theory.

Here is the reality.

1. Spelling. In the query letter itself, I’ve borne witness to some of the worst spelling gaffes imaginable. “Exiting story”, “expect mirikles” and “flare for writing”. The problem with a spelling error is once I’ve spotted one, I tend to dwell on it. It’s as if my eyes scan the remaining text, but my attention is firmly focused on the spelling error. Second or third language English speakers aside, poor spelling in the query letter, sample chapters or synopsis is a no-no of epic proportions.

2. Grammar. I’m the first to admit that my own writing tends to need an editor to check for grammatical inconsistencies. Although I’m able to pick up other’s grammar faux pas, I’m not as adept at my own. Don’t be proud. Send your work to an editor. Someone who gets paid, in actual cash, to edit work. And to all those who wish to break the conventional grammatical mould by doing something avant-garde, do so at your peril. Only attempt if your knowledge of the English language and its intracacies rival that of Shakespeare himself. Otherwise stick to convention.

3. The pitch. Yes you have to sell your book to a certain extent. Tell me why it’s different. Show me how your writing is original, unique, a literary voice that is in need of publishing on a grand scale. Refrain from telling me how fabulous your sister/aunt/mother/best friend from way back thought the book was. And that they’d be happy to recommend it. Please do not refer to your book in hyperbole – the best book ever written, the most exciting. Hype is just that.

4. Read the instructions. I ask for 3 sample chapters. Instead, from one aspirant non-fiction writer, I got a paragraph from the introduction. I ask for a brief bio on the author, and I get school day accolades. Publishers don’t put in instructions for fun. They’re there so we can make the best possible decision about your manuscript. Providing half the information, or the wrong information shows me you can’t even be bothered to read properly.

5. Learn to accept no. Publishers might well pass on your work. That is life. We don’t get every job we are interviewed for, we don’t get marriage proposals from everyone we date. Publishing is no different. It’s an alchemic, magical blend of timing, passion and best fit. If you’re a writer you’ll keep persisting. Take a note out of Stephen King’s book ‘On Writing’. He got hundreds of rejection slips. Did he throw a hissy fit or chuck away his typewriter? No, he learnt how to make his writing better.

All of that aside, I’m enjoying working through some potential scripts. Publishers need writers. Remember that.

Boa noite pessoal!

Para filtrar um texto, deixando somente os valores numéricos, pensei em realizar de duas formas, a primeira com WHILE e outra com CTE, mas como CTE se torna um pouco complexo para alguns, vou começar com WHILE:

Primeiro tenho meu texto, no caso estou utilizando a variável @PALAVRAS com um texto que encontrei na internet.

Tendo o texto, vou definir quais as variáveis que vou utilizar, assim tenho uma variável onde salvarei o resultado (@RESULTADO) da operação, uma variável para armazenar uma a uma as ’letras’ (@LETRA) da operação, uma variável para saber quantas ‘letras’ tenho no texto (@NUMERO) e outra para controle dos ‘loops’ da operação (@CONT).

Esqueci de dizem que é @ZERO e @NOVE, bem… elas irão armazenar os valores que identifica range inicial e final dos valores numéricos, no caso 0 (zero) e o 9 (nove) respectivamente.  A função UNICODE retorna o ‘valor decimal’ de um determinado caractere.

Uma observação importante é o valor inicial de @RESULTADO, pois como o valor inicial das variáveis é NULL, NULL somado a qualquer outros valor, nas configurações padrões do T-SQL, tem como resultado NULL, então precisamos estipular o valor inicial dele, assim como das outras variáveis.

Vamos agora ao laço de repetição, que percorrerá uma a uma as letras.

Agora temos a validação, onde verifico se a variável @LETRA esta em 0 (zero) e 9 (nove). Utilizando novamente a função UNICODE, que retorna o ‘valor decimal’ de um caractere.

Agora temos a primeira solução. No próximo artigo estarei detalhando a forma de realizar esta operação com CTE.

Disponíveis para download:

Função SOMENTE_NUMEROS (com WHILE):
http://www.4shared.com/file/152602109/18af521b/SOMENTE_NUMEROS_-_WHILE_-_Func.html

You can only do correlate subqueries in SELECT and WHERE clauses.

So, a subquery in FROM clause does not have access to the outer select.

select 	"Damage" , "IdAttackerWeapon" as w,
	(select sum(dd)
	from
		(select "Damage", "IdAttackerWeapon", abs(("Damage" - t."Damage")) as dd
		from fact_eventplayerdamage order by dd asc limit 5)
	t1)
from fact_eventplayerdamage t
group by "Damage", w

–

Reza

As promised, below are the before and after queries.  I sent the first one out to two agents, both passed.  Looking back, I’m not amazed by that fact.  More like upset with myself for sending out a clearly not-yet-ready query.  I thought it was…but I was wrong.

 The Before:

(note that I included a couple of lines customized to the agent, not included here)

Medical examiner Joe Cooper is a vampire with an insatiable appetite for booze, blood and women—and a hunger for justice. 

Joe would rather be drinking scotch.  Instead he’s up to his fangs in murdered Innocents, partnered with a suck-up profiler sent by the Council, and chasing rogue vampires on a killing spree during Baltimore’s peak tourist season.  Using his vampiristic abilities and skills acquired as a medical examiner, Joe tracks down the vamps responsible for the murders.  When he does, he discovers there’s more at stake than a group of bloodsuckers hell-bent on breaking all the laws that govern his kind.  And that the vampire calling the shots is the same one who turned him sixty years ago—a female with the darkest of blood running through her veins.  As the story draws to a close, Joe realizes that before you can knock down all your demons, you have to SET ‘EM UP, JOE. 

My 92,000 word manuscript, SET ‘EM UP, JOE, is an urban fantasy similar in style to Richelle Mead’s Dark Swan series; with flavors of noir similar to those found in The Dresden Files by Jim Butcher.  It is my first novel and the first of a proposed five book series featuring Joe Cooper. 

May I send my manuscript for your consideration?

Thank you for your time, 

Catherine Misener  (contact information was included with query)

I’m going to comment on why I think this one didn’t work, but first: 

The After

Dear, (again, I included a few lines customized to each agent I queried.  More on this when I compare the two queries.)

SET ‘EM UP, JOE is a 92,700 word paranormal noir similar in style to Jim Butcher’s The Dresden Files.  It is my first novel.

Being undead has its perks.  And for medical examiner Joe Cooper those include inhuman strength, good looks to spare, and the ability to get what he wants from any woman, anywhere, anytime.  Joe’s a vampire with a lust for booze, blood and the fairer sex.  And while Joe could spend all his nights with one hand on a bottle of scotch and the other on some curvy dame, being a member of the walking damned does carry baggage.  That tug on his conscience that for every ounce of blood he takes, he should give a little something back.  So to his other appetites, add a hunger for justice. 

Sure, Joe likes his blood direct from the source—and that doesn’t mean cud-chewing cows or big-eyed deer—but in his world, that doesn’t mean his mark has to die.  Take what you need and never leave the human worse for wear.  When others of his kind fail to follow that dictum, Joe doesn’t hesitate to point out the folly of their ways.  And in Baltimore, the latest place Joe calls home, more than one rogue vamp needs redirection. 

In this novel—the first of a proposed five book series—Joe finds himself up to his fangs in murdered Innocents and chasing rogue vampires on a killing spree during Charm City’s peak tourist season.  Using his vampiristic abilities and skills acquired as a medical examiner, Joe tracks down the vamps responsible for the murders.  When he does, he discovers there’s more at stake than a group of bloodsuckers hell-bent on breaking all the laws that govern his kind.  And that the vampire calling the shots is the same one who has hunted him for decades, the same one who turned him sixty years ago—a female with the darkest of blood running through her veins.  A nasty bit of goods he’s done everything he could to avoid, but the time for running is over.  Joe soon realizes that before you can knock down all your demons, you have to SET ‘EM UP, JOE. 

May I send you my manuscript for consideration? 

Thank you for your time, 

Catherine Misener (contact information, plus personal and character blogs included)

And there you go…two queries.  My thoughts on why I feel the second one is better, and the thought process behind my query next!

Wendy Burt-Thomas’s new book THE WRITER’S DIGEST GUIDE TO QUERY LETTERS was released in January 2009. Wendy was nice enough to share an interview she did while on a blog tour to promote her book with our #YAlitchat family. I hope you enjoy the interview. You can also visit Wendy online at www.AskWendy.wordpress.com.

1. Can you tell us about your book?

The book was a great fit for me because I’d been teaching “Breaking Into Freelance Writing” for about eight years. In the workshop, I covered a lot of what is in this book: writing query letters to get articles in magazines, to land an agent, or to get a book deal with a publisher. Since I’m a full-time freelance magazine writer and editor with two previous books, this was incredibly fun to write because it didn’t require tons of research. I was lucky enough to receive lots of great sample query letters from writers and authors that I use as “good” examples in the book. I wrote all the “bad” examples myself because I didn’t dare ask for contributions that I knew I’d be ripping apart! In addition to the ins and outs of what makes a good query, the book covers things like why (or why not) to get an agent, where to find one and how to choose one; writing a synopsis or proposal; selling different rights to your work; other forms of correspondence; and what editors and agents look for in new writers. It was really important to me that the book not be a dry, boring reference book, but rather an entertaining read (while still being chock full of information). I was thrilled that Writer’s Digest let me keep all the humor.

2. Why are query letters so important?

Breaking into the publishing world is hard enough right now. Unless you have a serious “in” of some kind, you really need a great query letter to impress an agent or acquisitions editor. Essentially, your query letter is your first impression. If they like your idea (and voice and writing style and background), they’ll either request a proposal, sample chapters, or the entire manuscript. If they don’t like your query letter, you’ve got to pitch it to another agency/publisher. Unlike a manuscript, which can be edited or reworked if an editor thinks it has promise, you only get one shot with your query. Make it count! I see a lot of authors who spend months (or years) finishing their book, only to rush through the process of crafting a good, solid query letter. What a waste! If agents/editors turn you down based on a bad query letter, you’ve blown your chance of getting them to read your manuscript. It could be the next bestseller, but they’ll never see it. My advice is to put as much effort into your query as you did your book. If it’s not fabulous, don’t send it until it is.

3. There’s an entire chapter in the book about agents. Do you think all new writers should get agents?

Probably 99% of new writers should get an agent. There are lots of reasons, but my top three are: 1) Many of the larger publishing houses won’t even look at unagented submissions now; 2) Agents can negotiate better rights and more money on your behalf; 3) Agents know the industry trends, changes and staff better than you ever could.

4. You’ve been a mentor, coach or editor for many writers. What do you think is the most common reason that good writers don’t get published?

Poor marketing skills. I see so many writers that are either too afraid, too uniformed, or frankly, too lazy, to market their work. They think their job is done when the write “the end” but writing is only half of the process. I’ve always told people who took my class that there are tons of great writers in the world who will never get published. I’d rather be a good writer who eats lobster than a great writer who eats hot dogs. I make a living as a writer because I spend as much time marketing as I do writing.

5. What are some of the biggest misconceptions that writers have about getting a book deal?

That they’ll be rich overnight, that they don’t need to promote their book once it’s published, that publishing houses will send them on world book tours, that people will recognize them at the airport. Still, you can make great money as an author if you’re prepared to put in the effort. If it wasn’t possible, there wouldn’t be so many full-time writers.

6. What must-read books do you recommend to new writers?

Christina Katz (author of “Writer Mama”) has a new book out called “Get Known Before the Book Deal” – which is fabulous. Also, Stephen King’s “On Writing” and David Morrell’s “Lessons from a Lifetime of Writing.” Anything by Anne Lamott or my Dad, Steve Burt.

7. What’s the biggest lesson you’ve learned as a full-time writer?

Seize every opportunity – especially when you first start writing. I remember telling someone about a really high-paying writing gig I got and he said, “Wow. You have the best luck!” I thought, “Luck has nothing to do with it! I’ve worked hard to get where I am.” Later that week I read this great quote: “Luck is when preparation meets opportunity.” It’s absolutely true. And writing queries is only about luck in this sense. If you’re prepared with a good query and/or manuscript, when the opportunity comes along you’ll be successful.

8. What did you enjoy most about writing this book?

Writing the “bad” query letters. I’ve read – and written! – so many horrible ones over the years that it was a little too easy to craft them. But misery loves company and we ALL love to read really bad query letters, right?

9. What do you want readers to learn from your book?

I want them to understand that while writing a good query letter is important, it doesn’t have to be overwhelming. You can break it down into parts, learn from any first-round rejections, and read other good queries to help understand what works. I also want them to remember that writing is fun. Sometimes new writers get so caught up in the procedures that they lose their original voice in a query. Don’t bury your style under formalities and to-the-letter formatting.

About Wendy Burt-Thomas

Wendy Burt-Thomas is a full-time freelance writer, editor and PR consultant. Her credentials include more than 1,000 published articles, reviews, short stories, poems and greeting cards. She’s also written three books: “Oh, Solo Mia! The Hip Chick’s Guide to Fun for One” (2001, McGraw-Hill); “Work It, Girl! 101 Tips for the Hip Working Chick” (2003, McGraw-Hill) and “The Writer’s Digest Guide to Query Letters” (2009, Writer’s Digest Books). Her fourth book, an update of “The Everything Creative Writing Book” (Adams Media) hits stores in April 2010.

I tried to watch the live feed of the New Moon Premiere in LA last night but the feed kept dropping off and the hosts were absolutely f*cking horrible. The show was hosted by Anya Marina who is a singer and has a song on the soundtrack. I don’t know who the guy was and I don’t really care.  He should have taken her mic away and stomped on it. Then I would go find out his name. During the interviews she kept asking everyone if they liked her song. OMG she was awful.

Enough ranting about a silly movie premiere.  I will say that Rob rocked the red carpet. hehehe. Okay back to writing. Well, we are headed in to the second half of NaNo and let me tell you I’m ready to hit that 50,000 word count so I can breathe. I have about 12,000 more words to come up with before I hit that magical number.  The sad thing is the story will not be complete but I’m really diggin’ my vamps so I’m going to continue until the story is finished. Probably have to jack it to 90,000 words or close to that number. Then the editing process will begin, but I really think I have a viable story. After I hit that fifty thousand number though I have to get my Time Jumper story ready to go out again. It will be back to the query process with the rewritten and amped up story. You will find me polishing my armour in preparation for the replies from agents and editors. One can always hope for a yes.