anthonykws
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Why Should I Make a Budget?




You say you know where your money goes and you don’t need it all written down to keep up with it? I issue you this challenge. Keep track of every penny you spend for one month and I do mean every penny.

You will be shocked at what the itty-bitty expenses add up to. Take the total you spent on just one unnecessary item for the month, multiply it by 12 for months in a year and multiply the result by 5 to represent 5 years.

That is how much you could have saved AND drawn interest in in just five years. That, my friend, is the very reason all of us need a budget.

If we can get control of the small expenses that really don’t matter to the overall scheme of our lives, we can enjoy financial success.

The little things really do count. Cutting what you spend on lunch from five dollars a day to three dollars a day on every workday in a five-day workweek saves $10 a week… $40 a month… $480 a year… $2400 in five years….plus interest.

See what I mean… it really IS the little things and you still eat lunch every day AND that was only one place to save money in your daily living without doing without one thing you really need. There are a lot of places to cut expenses if you look for them.

Set some specific long-term and short-term goals. There are no wrong answers here. If it’s important to you, then it’s an important period.

If you want to be able to make a down payment on a house, start a college fund for your kids, buy a sports car, take a vacation to Aruba… anything… then that is your goal and your reason to get a handle on your financial situation now.
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The company's analysts are using Amazon Athena to perform SQL queries against a recent subset of the overall data. The amount of data that is ingested into Amazon S3 has increased substantially over time, and the query latency also has increased. Which solutions could the company implement to improve query performance? (Choose two.) A.Use MySQL Workbench on an Amazon EC2 instance, and connect to Athena by using a JDBC or ODBC connector. Run the query from MySQL Workbench instead of Athena directly. B.Use Athena to extract the data and store it in Apache Parquet format on a daily basis. Query the extracted data. C.Run a daily AWS Glue ETL job to convert the data files to Apache Parquet and to partition the converted files. Create a periodic AWS Glue crawler to automatically crawl the partitioned data on a daily basis. D.Run a daily AWS Glue ETL job to compress the data files by using the .gzip format. Query the compressed data. 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Use server-side encryption with S3 managed encryption keys (SSE-S3) for the other datasets. C.Use server-side encryption with AWS KMS managed customer master keys (SSE-KMS CMKs) for the primary dataset. Use server-side encryption with S3 managed encryption keys (SSE-S3) for the other datasets. D.Use client-side encryption with AWS Key Management Service (AWS KMS) customer managed keys for the primary dataset. Use S3 client-side encryption with client-side keys for the other datasets. Answer: A QUESTION 127 A large telecommunications company is planning to set up a data catalog and metadata management for multiple data sources running on AWS. The catalog will be used to maintain the metadata of all the objects stored in the data stores. The data stores are composed of structured sources like Amazon RDS and Amazon Redshift, and semistructured sources like JSON and XML files stored in Amazon S3. The catalog must be updated on a regular basis, be able to detect the changes to object metadata, and require the least possible administration. Which solution meets these requirements? A.Use Amazon Aurora as the data catalog. Create AWS Lambda functions that will connect and gather the metadata information from multiple sources and update the data catalog in Aurora. Schedule the Lambda functions periodically. B.Use the AWS Glue Data Catalog as the central metadata repository. Use AWS Glue crawlers to connect to multiple data stores and update the Data Catalog with metadata changes. Schedule the crawlers periodically to update the metadata catalog. C.Use Amazon DynamoDB as the data catalog. Create AWS Lambda functions that will connect and gather the metadata information from multiple sources and update the DynamoDB catalog. Schedule the Lambda functions periodically. D.Use the AWS Glue Data Catalog as the central metadata repository. Extract the schema for RDS and Amazon Redshift sources and build the Data Catalog. Use AWS crawlers for data stored in Amazon S3 to infer the schema and automatically update the Data Catalog. Answer: D QUESTION 128 An ecommerce company is migrating its business intelligence environment from on premises to the AWS Cloud. The company will use Amazon Redshift in a public subnet and Amazon QuickSight. The tables already are loaded into Amazon Redshift and can be accessed by a SQL tool. The company starts QuickSight for the first time. During the creation of the data source, a data analytics specialist enters all the information and tries to validate the connection. An error with the following message occurs: "Creating a connection to your data source timed out." How should the data analytics specialist resolve this error? A.Grant the SELECT permission on Amazon Redshift tables. B.Add the QuickSight IP address range into the Amazon Redshift security group. C.Create an IAM role for QuickSight to access Amazon Redshift. D.Use a QuickSight admin user for creating the dataset. Answer: A QUESTION 129 A power utility company is deploying thousands of smart meters to obtain real-time updates about power consumption. The company is using Amazon Kinesis Data Streams to collect the data streams from smart meters. The consumer application uses the Kinesis Client Library (KCL) to retrieve the stream data. The company has only one consumer application. The company observes an average of 1 second of latency from the moment that a record is written to the stream until the record is read by a consumer application. The company must reduce this latency to 500 milliseconds. Which solution meets these requirements? A.Use enhanced fan-out in Kinesis Data Streams. B.Increase the number of shards for the Kinesis data stream. C.Reduce the propagation delay by overriding the KCL default settings. D.Develop consumers by using Amazon Kinesis Data Firehose. Answer: C QUESTION 130 A company needs to collect streaming data from several sources and store the data in the AWS Cloud. The dataset is heavily structured, but analysts need to perform several complex SQL queries and need consistent performance. Some of the data is queried more frequently than the rest. The company wants a solution that meets its performance requirements in a cost-effective manner. Which solution meets these requirements? A.Use Amazon Managed Streaming for Apache Kafka to ingest the data to save it to Amazon S3. Use Amazon Athena to perform SQL queries over the ingested data. B.Use Amazon Managed Streaming for Apache Kafka to ingest the data to save it to Amazon Redshift. Enable Amazon Redshift workload management (WLM) to prioritize workloads. C.Use Amazon Kinesis Data Firehose to ingest the data to save it to Amazon Redshift. Enable Amazon Redshift workload management (WLM) to prioritize workloads. D.Use Amazon Kinesis Data Firehose to ingest the data to save it to Amazon S3. Load frequently queried data to Amazon Redshift using the COPY command. Use Amazon Redshift Spectrum for less frequently queried data. Answer: B QUESTION 131 A manufacturing company uses Amazon Connect to manage its contact center and Salesforce to manage its customer relationship management (CRM) data. The data engineering team must build a pipeline to ingest data from the contact center and CRM system into a data lake that is built on Amazon S3. What is the MOST efficient way to collect data in the data lake with the LEAST operational overhead? A.Use Amazon Kinesis Data Streams to ingest Amazon Connect data and Amazon AppFlow to ingest Salesforce data. B.Use Amazon Kinesis Data Firehose to ingest Amazon Connect data and Amazon Kinesis Data Streams to ingest Salesforce data. C.Use Amazon Kinesis Data Firehose to ingest Amazon Connect data and Amazon AppFlow to ingest Salesforce data. 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How to earn from Instagram
आज सब लोगो को यह जानना है की Instagram Se Paise Kaise Kamaye यानि इंस्टाग्राम से घर बैठे पैसे कैसे कमाए , पर आपको इससे जुड़ी सारी Details बहुत कम ही जगह देखने को मिलेगी। आज में आपको ऐसे ही कुछ तरीके बताने वाला हु। जिससे आप घर बैठे सिर्फ दिन के 2 घंटे देकर Instagram से Side Income कर सकते है और बाद में आप अपने काम को कैसे Part Time से Full Time Business में Convert कर सकते है। पैसा कामना किसको अच्छा नहीं लगता है और जब पैसे घर बैठे कमाया जाये तो और भी अच्छा लगता है। Instagram आपको यह Opportunity देता है की आप घर बैठे इंस्टाग्राम से पैसे कमा पाए। पिछले दो सालो में Instagram में Active User Double हो चुके है , अभी इस समय 700 Million से भी ज्यादा लोग रोज इंस्टाग्राम यूज़ करते है। पिछले सात सालो में Instagram दुनिया में Top Social Media Platform बन चूका है और इसका Craze कब ख़तम होगा यह भी कोई नहीं बता सकता है। इससे आपको एक भरोसेमंद Platform मिल जाता है जिससे आपको future में कोइ Problem आये यह सोचना नहीं पड़ेगा। Instagram पे ज्यादा Active User होने के कारण आपको Customer ढूढ़ने की जरुरत नहीं पड़ेगी , सिर्फ आपको अपने Interest से जुड़ी हुई एक अच्छा और Interesting Page बनाना है और उसपे काम करते जाना है। Instagram Se Paise Kaise Kamaye Instagram से पैसे कमाने के ऐसे तो बहुत से तरीके है जिससे आप महीने के $200 से $10,000 तक कमा सकते है। आज में आपको उन्ही कुछ तरीको के बारे में बताने वाला हु जिससे Try करके आप भी कुछ दिनों में Instagram से पैसे कमा पाएंगे। यह तरीके का इस्तेमाल करके आप जान पाएंगे की Instagram Se Paise Kaise Kamaye Post sponsored content Become an affiliate marketer Sell your own products Sell Your Photo Account Selling for more reading follow the link https://thehindifacts.in/
The Person You Really Need to Marry
Tracy McMillan has written for a ton of the top TV shows and is most interested in human relationships. In her TED Talk (viewed more than 3 million times) she touches on how we find the person we REALLY need to marry. She starts off by telling us about how she thought of love when she was a child, citing the popular nursery rhyme. *k-i-s-s-i-n-g* But her life totally didn't end up like that. She's been married and divorced three times, and she says its because she consistently married the wrong guy for her. She says her husbands were awesome guys, but they just weren't the people she should be marrying. She brings up her philosophy of "marrying yourself." Here's what she means. In marrying yourself, you need to commit fully to yourself, Focus on you, and understanding you. Once you realize that you're whole and can stand all by yourself you'll see that you don't need any man or woman to complete you. She believes that so many marriages fail because the partners believe that they are lacking, and they're looking for someone to fill that gap. She goes deep into her love life (which is wild!) to show how she had to overcome all of the mistakes she made to get to where she is now. One thing she found from this practice that hit me pretty hard was that once loving herself, and she went on a few dates... She found that instead of wondering if the man liked HER, she was focusing on how SHE felt in his presence. She's listening to herself and her needs, not trying to prove anything to anybody. "I'm more interested in how I feel about me, than how he feels about me." What do you think about this philosophy? Would it work for you?
18-Year-Old Ties The Knot With His 71-Year-Old Soulmate.
Disclaimer: This is a true story, you guys. Almeda Errell didn't expect to fall in love. The 71-year-old just buried her eldest son, Robert, after losing him to diabetes complications. But, of all places, she met her soulmate at Robert's funeral - a 17-year-old Walmart cashier named Gary. "I wasn't looking for a young man, but Gary just came along," Almeda admitted in an interview with the Daily Mail. "I just knew straight away that he was the one." Gary and Almeda hadn't met before. Almeda was a widow with grown children and grandkids, and Gary was just finishing high school - and already in a rocky relationship with another 77-year-old woman. "We were always fighting," said Gary. "I fell into depression and was looking for a way out." The two were introduced at the funeral by Robert's widow, Lisa, who just so happened to be Gary's aunt. Lisa invited Gary to the funeral, and when he went to give Almeda his condolences, it apparently wasn't too long before sparks flew. "When I told Lisa that I liked Almeda, she said that she liked me too," Gary recalled. "And that she should get us together." For the most part, the pair says that family and friends gave the relationship their blessings. However, there was at least a little skepticism. "Some family members thought Gary was far too young for me, and that I must be crazy," said Almeda. "I told him I wasn't crazy, and that we loved each other." Once he turned 18, Gary proposed to her over the phone, and three weeks after becoming a couple, the pair were married in an intimate ceremony. Currently, the newlyweds live in Almeda's five-bedroom house with her 40-year-old daughter, DeAnna, and grandkids Aaron and Indianna, respectively aged 21 and 16. What do you guys think about extreme age gaps in dating? How would you respond if a friend or family member was in a relationship with a 50+ year age difference? Let me know what you think in the comments below. And for more bizarre but true stories of love, follow my Crazy Stupid Love collection!